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About Wakefern

Wakefern Food Corp. is the largest retailer-owned cooperative in the United States and supports its co-operative members' retail operations, trading under the ShopRite®, Price Rite®, The Fresh Grocer®, Dearborn Markets®, and Gourmet Garage® banners.

Employing an innovative approach to wholesale business services, Wakefern focuses on helping the independent retailer compete in a big business world. Providing the tools entrepreneurs need to stay a step ahead of the competition, Wakefern’s co-operative members benefit from the company’s extensive portfolio of services, including innovative technology, private label development, and best-in-class procurement practices.

The ideal candidate will have a strong background in designing, developing, and implementing complex projects, with focus on automating data processes and driving efficiency within the organization. This role requires a close collaboration with application developers, data engineers, data analysts, data scientists to ensure seamless data integration and automation across various platforms. The Data Integration & AI Engineer is responsible for identifying opportunities to automate repetitive data processes, reduce manual intervention, and improve overall data accessibility.

Essential Functions

• Participate in the development life cycle (requirements definition, project approval, design, development, and implementation) and maintenance of the systems.
• Implement and enforce data quality and governance standards to ensure the accuracy and consistency.
• Provide input for project plans and timelines to align with business objectives.
• Monitor project progress, identify risks, and implement mitigation strategies.
• Work with cross-functional teams and ensure effective communication and collaboration.
• Provide regular updates to the management team.
• Follow the standards and procedures according to Architecture Review Board best practices, revising standards and procedures as requirements change and technological advancements are incorporated into the >tech_ structure.
• Communicates and promotes the code of ethics and business conduct.
• Ensures completion of required company compliance training programs.
• Is trained – either through formal education or through experience – in software / hardware technologies and development methodologies.
• Stays current through personal development and professional and industry organizations.

Responsibilities

• Design, build, and maintain automated data pipelines and ETL processes to ensure scalability, efficiency, and reliability across data operations.
• Develop and implement robust data integration solutions to streamline data flow between diverse systems and databases.
• Continuously optimize data workflows and automation processes to enhance performance, scalability, and maintainability.
• Design and develop end-to-end data solutions utilizing modern technologies, including scripting languages, databases, APIs, and cloud platforms.
• Ensure data solutions and data sources meet quality, security, and compliance standards.
• Monitor and troubleshoot automation workflows, proactively identifying and resolving issues to minimize downtime.
• Provide technical training, documentation, and ongoing support to end users of data automation systems.
• Prepare and maintain comprehensive technical documentation, including solution designs, specifications, and operational procedures.

Qualifications

• A bachelor's degree or higher in computer science, information systems, or a related field.
• Hands-on experience with cloud data platforms (e.g., GCP, Azure, etc.)
• Strong knowledge and skills in data automation technologies, such as Python, SQL, ETL/ELT tools, Kafka, APIs, cloud data pipelines, etc.
• Experience in GCP BigQuery, Dataflow, Pub/Sub, and Cloud storage.
• Experience with workflow orchestration tools such as Cloud Composer or Airflow
• Proficiency in iPaaS (Integration Platform as a Service) platforms, such as Boomi, SAP BTP, etc.
• Develop and manage data integrations for AI agents, connecting them to internal and external APIs, databases, and knowledge sources to expand their capabilities.
• Build and maintain scalable Retrieval-Augmented Generation (RAG) pipelines, including the curation and indexing of knowledge bases in vector databases (e.g., Pinecone, Vertex AI Vector Search).
• Leverage cloud-based AI/ML platforms (e.g., Vertex AI, Azure ML) to build, train, and deploy machine learning models on a scale.
• Establish and enforce data quality and governance standards for AI/ML datasets, ensuring the accuracy, completeness, and integrity of data used for model training and validation.
• Collaborate closely with data scientists and machine learning engineers to understand data requirements and deliver optimized data solutions that support the entire machine learning lifecycle.
• Hands-on experience with IBM DataStage and Alteryx is a plus.
• Strong understanding of database design principles, including normalization, indexing, partitioning, and query optimization.
• Ability to design and maintain efficient, scalable, and well-structured database schemas to support both analytical and transactional workloads,
• Familiarity with BI visualization tools such as MicroStrategy, Power BI, Looker, or similar.
• Familiarity with data modeling tools.
• Familiarity with DevOps practices for data (CI/CD pipelines)
• Proficiency in project management software (e.g., JIRA, Clarizen, etc.)
• Familiarity with DevOps practices for data (CI/CD pipelines)
• Strong knowledge and skills in data management, data quality, and data governance.
• Strong communication, collaboration, and problem-solving skills.
• Ability to work on multiple projects and prioritize tasks effectively.
• Ability to work independently and in a team environment.
• Ability to learn new technologies and tools quickly.
• The ability to handle stressful situations.
• Highly developed business acuity and acumen.
• Strong critical thinking and decision-making skills.

Working Conditions & Physical Demands

This position requires in-person office presence at least 4x a week.

Compensation and Benefits

The salary range for this position is $75,868 - $150,644. Placement in the range depends on several factors, including experience, skills, education, geography, and budget considerations.

Wakefern is proud to offer a comprehensive benefits package designed to support the health, well-being, and professional development of our Associates. Benefits include medical, dental, and vision coverage, life and disability insurance, a 401(k) retirement plan with company match & annual company contribution, paid time off, holidays, and parental leave.

Associates also enjoy access to wellness and family support programs, fitness reimbursement, educational and training opportunities through our corporate university, and a collaborative, team-oriented work environment. Many of these benefits are fully or partially funded by the company, with some subject to eligibility requirements

We are looking for a highly motivated AI Engineer to join our IT team. This role is ideal for someone passionate about building real-world AI solutions and eager to work across the full AI technology stack—from model integration and retrieval pipelines to agentic AI workflows, multi-agent orchestration, and application-level features used by business teams. You will also contribute to data engineering efforts that feed AI capabilities, working alongside a modern analytics platform built on Microsoft Fabric.

As an AI Engineer, you will help design, develop, and deploy AI capabilities. You will contribute to production-grade AI features in areas such as Open-to-Buy planning, Sales Forecasting, Intelligent Order Management Systems (OMS), Product Copy Generation, and Image Generation.

This is a unique opportunity to work on meaningful, high-impact AI initiatives while implementing modern AI infrastructure, LLMOps practices, and scalable system design.

This role will work from our Greenwich, CT office and report to the Senior Director of System Integration & Operation on our current hybrid schedule, 3 days in office and 2 days remote.

Key Responsibilities:

AI Application Development

Build and maintain AI-powered features including:

• Open-to-Buy optimization and inventory planning models
• Sales forecasting and demand prediction solutions
• Intelligent OMS features for routing, allocation, and automation
• Marketing AI tools such as product copy generation and AI-assisted image generation

Integrate custom and foundation LLMs into internal applications using API and SDK interfaces, leveraging structured outputs, function/tool calling, and prompt caching to optimize reliability and cost.

RAG, GraphRAG, + Vector DB Engineering

• Develop retrieval pipelines using vector embeddings and similarity search (Azure AI Search, FAISS, Pinecone, or equivalent).
• Implement chunking, embedding, indexing, query routing, and relevance-tuning strategies, including advanced reranking and hybrid search techniques.
• Maintain a high-quality knowledge base to support AI features via Retrieval-Augmented Generation.
• Explore and implement GraphRAG patterns to improve knowledge retrieval over structured enterprise data and entity relationships.

AI Agents & Orchestration

• Design and build AI agents capable of planning, tool use, and multi-step reasoning using frameworks such as LangGraph, PydanticAI, CrewAI, or Google ADK.
• Implement Model Context Protocol (MCP) and Agent-to-Agent (A2A) protocol integrations to connect AI agents with internal tools, APIs, data systems, and other agents in a standardized, interoperable way.
• Build guardrails, evaluation frameworks, and human-in-the-loop checkpoints to ensure reliable and safe agent behavior in production.

AI Infrastructure & System Architecture

• Maintain private cloud LLM instance landscape, ensuring secure and efficient usage.
• Assist in deploying scalable inference pipelines, batching, and caching layers.
• Collaborate with DevOps and Data Engineering on CI/CD, model deployment workflows, monitoring, and integration with the Microsoft Fabric data platform (including Fabric MCP for agent-to-data connectivity).

Data Engineering, Pipelines & Model Training

• Clean, transform, and prepare datasets for ML/AI pipelines; contribute to data engineering workflows including ELT pipeline design, medallion architecture patterns, and data transformation within the Lakehouse layer.
• Train, validate, and fine-tune models where appropriate (LLMs, forecasting models, classification models, etc.); familiar with parameter-efficient techniques such as LoRA and QLoRA.
• Evaluate model performance and optimize latency, accuracy, and cost using LLM evaluation and observability frameworks (e.g., RAGAS, LangSmith, Langfuse, Helicone, or custom evals); manage prompt versioning and regression testing.

Required Qualifications:

• Bachelor’s degree in Computer Science, Data Science, AI/ML, Engineering, or related field.
• Strong foundations in Python, data structures, and machine learning concepts.
• Comfortable working with LLM APIs, embeddings, vector databases, and RAG patterns; exposure to agentic patterns, tool use, and GraphRAG concepts is a strong plus.
• Familiarity with cloud environments (Azure preferred; AWS or GCP also acceptable).
• Understanding of systems diagrams, architecture patterns, and AI infrastructure components.
• Exposure to SQL/NoSQL databases.
• Exposure to data engineering concepts such as ELT/ETL pipelines, data transformation, and data modeling.
• Awareness of responsible AI principles including bias detection, fairness, and model interpretability.
• Awareness of AI agent frameworks and orchestration concepts (e.g., LangGraph, PydanticAI, Semantic Kernel, CrewAI, or Google ADK).
• Familiarity with prompt engineering best practices including chain-of-thought, few-shot prompting, and structured output design.

Preferred Qualifications:

• Familiarity with Microsoft Fabric (OneLake, Lakehouse, Spark notebooks, semantic models) and Power BI; experience with Fabric MCP integrations is a strong differentiator.
• Experience implementing MCP (Model Context Protocol) servers or A2A (Agent-to-Agent) protocol endpoints, or integrating AI agents with external tools and APIs.
• Exposure to multimodal AI capabilities (vision-language models) for applications such as product image analysis or document understanding.
• Experience building small AI apps, demos, or tools—portfolio/GitHub encouraged.

What you'll Gain:

• Hands-on impact in designing enterprise AI capabilities from the ground up.
• Opportunities to work with cutting-edge LLM technologies in a private, secure environment, alongside a modern Microsoft Fabric data platform.
• A chance to shape AI products used across supply chain, marketing, and e-commerce.

Company Overview:

Established in 2005, Marc Fisher Footwear company is a leading full-service, product-driven fashion footwear company with knowledge and expertise in design, sales, sourcing, distribution and marketing – all with dedicated and strategic direction for each brand within the portfolio, which includes GUESS, G by Guess, Nine West, Tommy Hilfiger, Earth, Calvin Klein, Kenneth Cole Men's, Hunter Boots, Rockport, Bandolino, indigo rd., Unisa, and Easy Spirit along with the namesake brands – Marc Fisher and Marc Fisher LTD.

Our diverse portfolio of globally recognized brands – available domestically and internationally via wholesale and retail channels – consistently meets the widest range of consumers’ fashion footwear needs, from classic to contemporary, sport to dress, men’s to women’s. Headquartered in Greenwich, Connecticut, with showrooms in New York City, Marc Fisher Footwear is sold worldwide through department stores, specialty stores and e-commerce channels.

Marc Fisher Footwear is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, sex, sexual orientation, age, status as a protected veteran, among other things, or status as a qualified individual with a disability. EEO Employer/Vet/Disabled.

**Candidate must be willing to go into office 3 days a week**

Senior Full-Stack AI & Data Engineer – Contract

RBA is an established leader and trusted partner for enterprise and mid-size organizations seeking to transform their business through technology solutions. As a Digital and Technology consultancy, we combine strategic insight with technical expertise to deliver impactful, scalable solutions that align with business goals. We take pride in working with some of the most recognized companies in our market—while fostering a culture that blends challenging career opportunities with a collaborative, fun work environment.

We are seeking a Senior Full-Stack AI & Data Engineer to join our growing Data & AI practice, supporting a high-impact client. In this role, you will lead the design and development of end-to-end AI-powered applications that drive personalization, predictive analytics, and next-generation digital experiences.

You’ll partner with business stakeholders, product teams, and engineers to build production-grade AI solutions—from data pipelines and model development to APIs and user-facing applications. The ideal candidate brings deep expertise across the full stack, modern data platforms, and generative AI technologies, with a passion for solving complex business challenges through innovative solutions.

Responsibilities

• Design and develop end-to-end AI-powered applications, including backend APIs and user-facing interfaces, to enable scalable and intuitive AI solutions.
• Build and maintain robust APIs using technologies such as Node.js, NestJS, or FastAPI, and develop modern web applications using React or similar frameworks.
• Develop, fine-tune, and deploy machine learning models using frameworks such as PyTorch and Scikit-learn.
• Implement advanced generative AI solutions, including Retrieval-Augmented Generation (RAG) pipelines and multi-modal AI applications.
• Design and build agentic AI systems using frameworks such as LangChain, enabling multi-step reasoning, tool use, and automation.
• Architect and optimize end-to-end data pipelines (ETL/ELT) using Python, SQL, and orchestration tools such as Airflow.
• Manage and integrate data workflows within Snowflake, leveraging technologies such as Snowpark or Cortex.
• Implement monitoring and observability for AI systems, including tracking model performance, drift, latency, and reliability.
• Design and deploy cloud-native solutions using Docker, Kubernetes, and CI/CD pipelines across AWS, Azure, or GCP.
• Collaborate with business stakeholders to translate data into actionable insights and intelligent applications.
• Contribute to DevOps best practices, including infrastructure-as-code (Terraform) and automated testing.
• Mentor junior engineers and promote best practices in AI ethics, data governance, and code quality.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• 5+ years of experience across full-stack development, including backend (Node.js/Python) and frontend frameworks (React or similar).
• Strong experience designing and building data pipelines and modern data platforms, including expertise in SQL and data modeling.
• Proven experience deploying AI/ML solutions in production environments, including MLOps and model lifecycle management.
• Hands-on experience with generative AI technologies, including LLMs, prompt engineering, and RAG architectures.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Strong understanding of DevOps practices, including CI/CD, containerization, and infrastructure-as-code (Terraform).
• Excellent communication skills and ability to work effectively in client-facing environments.

Preferred Qualifications

• Experience with Snowflake, including Snowpark, Cortex, or similar data platform capabilities.
• Experience building agent-based AI systems or working with frameworks such as LangChain.
• Familiarity with vector databases and semantic search architectures.
• Experience developing mobile applications using React Native or Flutter.
• Knowledge of mobile architecture, UI/UX principles, and API integration patterns.
• Experience deploying applications to Apple App Store or Google Play Store.
• Familiarity with security and authentication protocols, including OAuth2, biometric authentication, and secure data handling.
• Cloud or data platform certifications (AWS, Azure, GCP, Snowflake, or similar).

Leadership & Culture

• Demonstrate leadership through mentorship, technical guidance, and promoting engineering best practices.
• Balance innovation with pragmatism—able to work across cutting-edge AI solutions and foundational data engineering tasks.
• Thrive in a collaborative, fast-paced consulting environment with a strong focus on client impact and delivery excellence.

Python AI Engineer (Prompt & Agentic Systems)

Location: Hybrid –Atlanta, GA (3 days a week onsite)

Client: Retail client

About the Role

We’re looking for a hands-on engineer who can build AI-enabled applications end-to-end using Python, with strong skills in prompt engineering and agentic system design (multi-agent/orchestrated AI workflows). You’ll design, develop, and productionize intelligent features—ranging from retrieval-augmented generation (RAG) to autonomous tasking agents integrated with internal tools and APIs.

Key Responsibilities

• Design & Build AI Services: Develop Python-based back-end services that integrate LLMs for reasoning, extraction, summarization, and decision support.
• Prompt Engineering: Craft, version, and evaluate prompts/system instructions; design guardrails, test prompt variants, and optimize for reliability, latency, and cost.
• Agentic Systems: Architect and implement autonomous/multi-agent workflows—planning, tool-use, memory, error recovery, and human-in-the-loop controls.
• RAG Pipelines: Implement document ingestion, chunking, embeddings, vector search (semantic/re-ranking), and grounding strategies.
• Evaluation & Observability: Define metrics and build eval suites for quality (accuracy, factuality, safety), and establish tracing/telemetry for LLM calls.
• API & Tool Integrations: Enable agents to use tools (internal APIs, search, databases, workflow engines); handle auth, rate limits, and fallbacks.
• MLOps / AIOps: Package, containerize, and deploy services (Docker/K8s); manage keys, secrets, CI/CD; support canary rollouts and cost governance.
• Security & Compliance: Apply data privacy principles, PII handling, redaction, prompt injection defenses, and audit logging.
• Cross-Functional Collaboration: Partner with product, data, and security teams to translate requirements into reliable AI features.

Required Qualifications

• Strong Python (typing, async, testing, packaging) and experience building production APIs/services (FastAPI/Flask).
• Hands-on with LLMs (OpenAI, Azure OpenAI, Anthropic, etc.) and embedding/RAG workflows.
• Proven prompt engineering experience (few-shot strategies, tool-use instructions, output schemas, function/tool calling).
• Experience with agent frameworks or custom agent orchestration (e.g., LangGraph/LangChain/AutoGen, or in-house equivalents).
• Vector databases (e.g., FAISS, Chroma, Pinecone, Weaviate) and search relevance tuning.
• Familiar with MLOps/DevOps: Docker, CI/CD, monitoring (Prometheus/Grafana), logging (OpenTelemetry), secrets management.
• Testing & Evals: unit/integration tests, offline evals, golden datasets, regression checks.
• Practical understanding of AI safety/guardrails (prompt injection, data leakage, jailbreak prevention).

Nice to Have

• Experience with Azure (or AWS/GCP) AI services, key vaults, and networking.
• Knowledge of Model Context Protocol (MCP) or tool-server patterns for secure tool access.
• Experience with retrievers (BM25, hybrid search), re-rankers, or LlamaIndex/LangChain.
• Familiarity with streaming UIs and structured outputs (JSON, Pydantic schemas).
• Background in LLM finetuning, RLHF/DPO, or synthetic data generation.
• Front-end basics for AI UX (React/Next.js) or chat UI patterns.
• Domain knowledge in HR/ATS, customer support, or internal enterprise workflows.

Must be local to TX

Role Overview

• He’s ideally looking for someone with 13+ years of experience, strong architecture depth, and the ability to clearly explain designs.
• Must have experience using AI is used in day‑to‑day development.
• Must have experience as a API Developer to lead the development and deployment of our backend services. In this role, you will be the bridge between our PostgreSQL database and React frontend, responsible not only for writing high-performance Python code but also for architecting the CI/CD pipelines that bring our applications to life. You will ensure our integration layers are scalable, secure, and automatically deployed.

Job Summary

We are seeking a Principal-level Full Stack Lead Developer with 13+ years of experience to drive high-priority engineering workstreams. This role is for a technical heavyweight who can lead new projects in parallel with existing leadership while maintaining exceptional architecture depth. You will be responsible for the full lifecycle of high-performance FastAPI and React applications, ensuring they are resilient, observable, and scalable. We expect a leader who views AI development tools as a force multiplier for velocity and can clearly articulate complex design decisions to stakeholders.

Key Responsibilities

• Project Sovereignty: Independently lead and deliver new, complex workstreams from inception to launch, acting as a technical peer to existing leadership (e.g., Sai).
• System Architecture: Design and defend distributed microservices and event-driven architectures. You must be able to clearly whiteboard and communicate design patterns to both technical and non-technical audiences.
• Hands-on Execution: Maintain high-velocity output of clean, production-grade code using FastAPI (Python) and React (TypeScript).
• Platform Reliability: Architect and implement global Error Handling frameworks, centralized Logging (e.g., OpenTelemetry, ELK), and API Management strategies including Rate Limiting and versioning.
• Event-Driven Messaging: Oversee the implementation of asynchronous service communication using ActiveMQ or AWS EventBridge.
• AI-Augmented SDLC: Deeply integrate AI coding tools (e.g., CloudCode, Cursor, GitHub Copilot) into daily workflows to accelerate prototyping, refactoring, and automated testing.
• Engineering Mentorship: Foster a culture of excellence through rigorous code reviews and by unblocking senior engineers on complex technical hurdles.
• Product Collaboration: Work closely with Product Managers to turn high-level roadmaps into technical reality, providing accurate estimates and identifying technical risks early.

Required Skills & Qualifications

• Experience:13+ years of professional software development with a proven track record of leading large-scale products.
• Tech Stack Mastery: Expert-level FastAPI (Async Python) and modern React (Hooks, TypeScript, Performance Profiling).
• Advanced Governance: Hands-on experience with API Gateway patterns, request throttling, and securing distributed systems (OAuth2/JWT).
• Observability & Messaging: Deep knowledge of structured logging, distributed tracing, and message brokers (ActiveMQ or EventBridge).
• AI Tooling: Advanced proficiency in using AI tools for Fast Development to reduce manual overhead and multiply team output.
• Database & Infrastructure: Expert-level PostgreSQL (tuning/indexing), Redis (for caching/rate-limiting), and container orchestration (Kubernetes/Docker).
• Communication: Exceptional ability to translate technical "scars" and architectural risks into clear business impact.

Be a part of our success story. Launch offers talented and motivated people the opportunity to do the best work of their lives in a dynamic and growing company. Through competitive salaries, outstanding benefits, internal advancement opportunities, and recognized community involvement, you will have the chance to create a career you can be proud of. Your new trajectory starts here at Launch!

The Role:

Launch is actively seeking a visionary Solutions Architect / Principal Software Engineering Lead (AI) to design and deliver modern engineering and applied AI solutions across client engagements. This role blends deep hands‑on engineering, architectural leadership, AI system design, and client advisory. You will operate across system design, production‑grade engineering, multi‑agent architectures, cloud platform strategy, and the development of Launch’s AI practice.

Responsibilities Include:

Architecture & Technical Strategy

• Define the technical direction for client engagements end-to-end: discovery, design, build, and production hardening.
• Assess client technology ecosystems and identify high-impact opportunities for AI/ML integration.
• Lead architecture reviews, design sessions, and technology selection across cross-functional stakeholder groups.
• Translate ambiguous business problems into concrete engineering plans with clear scope, milestones, and risk callouts.

AI Engineering & Delivery

• Architect production agentic systems including multi-agent orchestration, agent harnesses, skill/tool composition, human-in-the-loop checkpoints, and inter-agent communication protocols (e.g., A2A, MCP).
• Build and govern MCP server ecosystems: design, deploy, and secure Model Context Protocol integrations connecting AI agents to enterprise data sources, internal APIs, and third-party platforms.
• Define agent skill and capability frameworks including reusable skill libraries, prompt engineering standards, and evaluation harnesses for consistent agent behavior across engagements.
• Architect RAG pipelines, fine-tuning workflows, and model lifecycle infrastructure (training, serving, experiment tracking) as foundational components of agentic systems.
• Integrate AI platforms and APIs (Azure OpenAI, Amazon Bedrock, Anthropic, Vertex AI) into production systems with enterprise-grade reliability, cost governance, and observability.
• Establish AI-native development practices: embed tools such as Claude Code, Cursor, and GitHub Copilot into team workflows with standards for AI-assisted code review, test generation, and documentation.
• Design evaluation and observability infrastructure including LLM eval frameworks, red-teaming, behavioral drift detection, and production monitoring across tool call chains, latency, and failure modes.
• Apply responsible AI governance: define guardrails, access controls, and audit patterns for agentic workflows in enterprise environments including scope containment and escalation paths.

Hands-On Engineering

• Write production code and lead by example — this role requires someone who is still close to the code.
• Design cloud-native architectures across multiple hyperscalers (AWS and Azure primarily) microservices, event-driven systems, serverless, and containerized workloads.
• Define and implement infrastructure-as-code using tools such as Terraform, Pulumi, CloudFormation, or Bicep.
• Design and optimize CI/CD pipelines, GitOps workflows, and container orchestration using Docker and Kubernetes.
• Establish observability and reliability practices using tools such as Datadog, Prometheus, Grafana, CloudWatch, or Azure Monitor.
• Drive security-by-design across the delivery lifecycle including IAM, network architecture, secrets management, and compliance automation.

Leadership & Client Advisory

• Lead engineering teams ranging from small squads to 10+ person delivery teams, scaling leadership approach to the needs of each engagement.
• Mentor and develop engineers at all levels through code reviews, pairing, and design coaching.
• Operate as a trusted advisor to client technical leadership and executive stakeholders. Communicate trade-offs clearly and build confidence.
• Influence without direct authority — driving alignment across cross-functional teams through technical credibility and stakeholder management.
• Lead discovery and requirements elicitation, surfacing the underlying business need beyond the stated request.
• Produce clear written artifacts: technical proposals, architecture decision records, SOWs, and executive-level status communication.
• Grow client relationships and identify follow-on opportunities through proposal contributions and delivery-driven account expansion.
• Contribute to Launch's growth — practice development, thought leadership, and hiring.

Qualifications:

Must-Haves:

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field.
• 10+ years in software engineering with demonstrated experience in architecture and technical leadership roles.
• 3+ years hands-on with AI/ML in production. Broad fluency across generative AI (LLMs, RAG, fine-tuning, agents), MLOps (model serving, pipelines, experiment tracking), and AI-integrated product development.
• Consulting or client-facing delivery experience with a proven ability to integrate into client organizations and establish credibility with technical and executive stakeholders.
• Full-stack engineering capability across frontend, backend, infrastructure, and data layers. Proficiency in multiple modern languages (e.g., Python, TypeScript/Node.js, C#/.NET, Java, or Go) with the ability to move between them as engagements require.
• Multi-hyperscaler depth across AWS and Azure, including their respective AI/ML service ecosystems (Bedrock, SageMaker, Azure OpenAI, Azure ML). GCP experience is a plus.
• Strong fundamentals in distributed systems, event-driven architecture, API design, and DevOps/platform engineering.
• Experience leading engineering teams in agile delivery environments.
• Business acumen with the ability to connect architecture decisions to cost, timeline, and organizational impact.
• Executive presence and communication skills effective with both technical and non-technical audiences.
• Proven ability to operate in ambiguous environments and adapt to diverse client cultures.

Strong Differentiators

• Experience contributing to the development of AI engineering practices, reusable frameworks, or internal accelerators within a consulting or enterprise environment.
• Experience advising C-suite or VP-level stakeholders on AI strategy, investment prioritization, and organizational readiness.
• Depth with agentic AI frameworks (LangChain, LangGraph, LangSmith, LlamaIndex, Semantic Kernel, CrewAI) and emerging standards like MCP (Model Context Protocol).
• Experience with enterprise data platforms (Databricks, Snowflake, BigQuery) in the context of AI/ML workloads.
• Cloud architecture certifications across AWS and Azure (AWS SA Professional, Azure Solutions Architect Expert).
• Published writing, open-source contributions, or conference speaking that demonstrates thought leadership in AI or software architecture.
• Domain depth in industries such as healthcare, financial services, retail, or public sector.

Compensation & Benefits:

As an employee at Launch, you will grow your skills and experience through a variety of exciting project work (across industries and technologies) with some of the top companies in the world! Our employees receive full benefits—medical, dental, vision, short-term disability, long-term disability, life insurance, and matched 401k. We also have an uncapped, take-what-you-need PTO policy. The anticipated base wage range for this role is $190,000 to $230,000. Education and experience will be highly considered, and we are happy to discuss your wage expectations in more detail throughout our internal interview process.

At Rite-Hite, your work makes an impact. As the global leader in loading dock and door equipment, we design and deliver solutions that keep our customers safe, secure, and productive. Here, you'll find innovation, stability, and the chance to grow your career as part of a team that's always looking ahead.

ESSENTIAL DUTIES AND RESPONSIBILITIES

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily.

• Design and build AI-powered applications using Large Language Models (LLMs) for enterprise use cases.
• Develop Retrieval-Augmented Generation (RAG) solutions using structured and unstructured enterprise data such as documents, manuals, tickets, ERP data, and knowledge bases.
• Build and orchestrate AI agents that can reason, plan, and interact with tools, APIs, and workflows.
• Implement guardrails for AI systems including prompt safety, data protection, hallucination mitigation, access control, and output validation.
• Work with multimodal AI models including text, image, and video use cases such as video analysis, summarization, and optimization.
• Integrate AI solutions with existing enterprise systems such as Salesforce, ERP platforms, data lakes, APIs, and internal applications.
• Partner with security and compliance teams to ensure responsible AI usage, data privacy, and governance.
• Prototype quickly, then harden solutions for production with monitoring, logging, evaluation, and performance optimization.
• Mentor and upskill existing developers on AI concepts, patterns, and best practices.

Required Skills & Experience

• 5+ year of full stack development experience.
• Strong software engineering background with experience building production-grade applications.
• Hands-on experience with modern LLM platforms such as OpenAI, Azure OpenAI, Anthropic, or similar.
• Practical experience building RAG pipelines using vector databases and embedding models.
• Experience with prompt engineering, prompt versioning, and evaluation techniques.
• Solid Python experience for AI development.
• Experience integrating AI services with REST APIs, microservices, and cloud-native architectures.
• Familiarity with cloud platforms such as AWS or Azure, including deployment, scaling, and security concepts.
• Understanding of data formats such as JSON, XML, and document-based data.
• Ability to translate business problems into AI-driven technical solutions.

Preferred Qualifications

• Experience with vector databases such as Pinecone, FAISS, Weaviate, or similar.
• Familiarity with frameworks such as LangChain, LlamaIndex, Semantic Kernel, or equivalent orchestration tools.
• Experience implementing AI safety controls, policy enforcement, and evaluation frameworks.
• Exposure to video or image models and multimodal AI use cases.
• Experience working in enterprise environments with security, compliance, and change management considerations.
• Prior experience mentoring or leading developers in new technical domains.

What We Offer

At Rite-Hite, we take care of our people - because when you're supported, you can do your best work. Our benefits are designed to support your health, your future and your life outside of work:

• Health & Well-being: Comprehensive medical, dental, and vision coverage, plus life and disability insurance. A robust well-being program with an opportunity to receive an extra day off and more.

• Financial Security: A strong retirement savings program with 401(k), company match, and profit sharing.

• Time for You: Paid holidays, vacation time, and personal/sick days each year.

Join us and build a career where you're supported - at work and beyond.

Rite-Hite is proud to be an Equal Opportunity Employer. We consider all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic under federal, state, or local law.In accordance with VEVRAA, we are committed to providing equal employment opportunities for protected veterans.We are also committed to maintaining a drug-free workplace for the safety of our employees and customers.

Join the team leading the next evolution of virtual care.

At Teladoc Health, you are empowered to bring your true self to work while helping millions of people live their healthiest lives.

Here you will be part of a high-performance culture where colleagues embrace challenges, drive transformative solutions, and create opportunities for growth. Together, we're transforming how better health happens.

Summary of Position

As a Staff Software Engineer, you are a senior individual contributor who leads the design and delivery of significant platform features and raises the bar for engineering quality across the team. You'll work handson in code-designing APIs and data flows, building services in Python/FastAPI and React frontends, and guiding solutions from idea to production. You'll mentor engineers, influence architecture and standards within and adjacent to your team, and partner closely with product and design to achieve clear, measurable outcomes. This role blends deep implementation work with pragmatic technical leadership by example.

Essential Duties and Responsibilities

• Lead technical design for platform features and services, breaking ambiguous requirements into clear, incremental designs and stories for your team and adjacent partners.

• Implement backend services in Python/FastAPI and React frontends end-to-end, owning a continuous stream of stories from idea to production.

• Define and use clear API contracts and data flows between services and UIs, creating patterns and templates others can follow.

• Champion high-quality engineering practices, including code reviews, documentation, and maintainable, testable designs.

• Develop and improve automated testing (unit, integration, endtoend) and integrate these into everyday development and CI.

• Improve CI/CD pipelines and release workflows for your team so the team can ship small, safe changes frequently and confidently.

• Own the operational lifecycle of the features and services you build, including monitoring, observability, on-call participation, and incident follow-up.

• Design and implement secure-by-default solutions, including robust authentication/authorization, input validation, and safe handling of sensitive data.

• Identify and address reliability and performance risks early, proposing concrete technical improvements and sequencing them into the roadmap.

• Mentor and unblock engineers through pairing, design discussions, and clear feedback; influence without formal authority.

• Partners with product/design to shape requirements into incremental deliverables; escalates tradeoff decisions; proposes sequencing that optimizes value/risk.

The time spent on each responsibility reflects an estimate and is subject to change dependent on business needs.

Supervisory Responsibilities

No

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, or related field; equivalent work experience is acceptable.

• 7+ years of experience in software engineering.

• Strong proficiency with Python and modern web backends (FastAPI, Flask, Django, or similar) and solid understanding of HTTP, API design, and data modeling.

• Significant experience with React (or a comparable SPA framework) and building production frontends that talk to backend APIs.

• Demonstrated ability to own features end-to-end in a small team: from shaping requirements through design, implementation, testing, deployment, and support.

• Experience designing and working with distributed systems or multi-service architectures (e.g., service boundaries, async jobs, integration patterns).

• Solid understanding of observability and operations for production systems (metrics, logs, traces, dashboards, alerting, incident response).

• Strong understanding of security fundamentals (authentication, authorization, secure data handling) and how they apply to web services and UIs.

• Deep familiarity with automated testing and CI/CD, and a track record of improving engineering workflows and quality.

• Excellent communication and collaboration skills; comfortable working closely with product, design, and other stakeholders.

• Proven ability to provide technical leadership in a hands-on way: unblocking others, making clear decisions, and raising the bar through code and reviews.

Bonus Qualifications

• Experience in early-stage or small platform teams where engineers wear multiple hats and balance shipping with building foundations.

• Experience with Azure and containerized deployments (or similar cloud-native environments).

• Experience building platforms (developer platforms, data platforms, or similar) that serve multiple product teams.

• Exposure to AI/ML or data-intensive applications (e.g., integrating with model inference APIs, data pipelines, or analytical data stores).

The base salary range for this position is$180,000 - $200,000. In addition to a base salary, this position is eligible for a performance bonus and benefits (subject to eligibility requirements) listed here: Teladoc Health Benefits 2026.Total compensation is based on several factors including, but not limited to, type of position, location, education level, work experience, and certifications.This information is applicable for all full-time positions.

#LI-SS2 #LI-Remote

We follow a Flexible Vacation Policy, intended for rest, relaxation, and personal time. All time off must be approved by your manager prior to use. You will also receive 80 hours of Paid Sick, Safe, and Caregiver Leave annually. This applies to full-time positions only. If you are applying for a part-time role, your recruiter can provide additional details.

As part of our hiring process, we verify identity and credentials, conduct interviews (live or video), and screen for fraud or misrepresentation. Applicants who falsify information will be disqualified.

Teladoc Health will not sponsor or transfer employment work visas for this position. Applicants must be currently authorized to work in the United States without the need for visa sponsorship now or in the future.

Why join Teladoc Health?

• Teladoc Health is transforming how better health happens. Learn how when you join us in pursuit of our impactful mission.

• Chart your career path with meaningful opportunities that empower you to grow, lead, and make a difference.

• Join a multi-faceted community that celebrates each colleague's unique perspective and is focused on continually improving, each and every day.

• Contribute to an innovative culture where fresh ideas are valued as we increase access to care in new ways.

• Enjoy an inclusive benefits program centered around you and your family, with tailored programs that address your unique needs.

• Explore candidate resources with tips and tricks from Teladoc Health recruiters and learn more about our company culture by exploring #TeamTeladocHealth on LinkedIn.

As an Equal Opportunity Employer, we never have and never will discriminate against any job candidate or employee due to age, race, religion, color, ethnicity, national origin, gender, gender identity/expression, sexual orientation, membership in an employee organization, medical condition, family history, genetic information, veteran status, marital status, parental status, or pregnancy). In our innovative and inclusive workplace, we prohibit discrimination and harassment of any kind.

Teladoc Health respects your privacy and is committed to maintaining the confidentiality and security of your personal information. In furtherance of your employment relationship with Teladoc Health, we collect personal information responsibly and in accordance with applicable data privacy laws, including but not limited to, the California Consumer Privacy Act (CCPA). Personal information is defined as: Any information or set of information relating to you, including (a) all information that identifies you or could reasonably be used to identify you, and (b) all information that any applicable law treats as personal information. Teladoc Health's Notice of Privacy Practices for U.S. Employees' Personal information is available at this link.

Join the team leading the next evolution of virtual care.

At Teladoc Health, you are empowered to bring your true self to work while helping millions of people live their healthiest lives.

Here you will be part of a high-performance culture where colleagues embrace challenges, drive transformative solutions, and create opportunities for growth. Together, we're transforming how better health happens.

Summary of Position

The Principal AI Security Engineer is a senior technical leader on the AI Security team, responsible for designing, building, and operating security controls for generative AI and Machine Learning (ML) systems across their full lifecycle: data, training, deployment, and runtime.

This role is deeply hands-on: you will work directly with data science, MLOps, platform, devops and application teams to secure LLMs, RAG systems, AI agents, and AI-enabled products. You will also lead the intake and review process for AI use cases, helping the organization adopt AI safely and at scale in a highly regulated environment.

The ideal candidate combines:

* Strong security engineering and cloud architecture experience

* Deep, current familiarity with modern AI/LLM tooling and practices

* Familiar and can cover basic coding within the AI tooling space (python, others)

* The ability to communicate clearly with senior leadership and influence enterprise-wide strategy

Essential Duties and Responsibilities

Secure AI / ML platforms and workloads

* Lead security architecture and threat modeling for AI/ML systems, including LLMs, RAG pipelines, agents, and AI-powered applications.

* Design and implement security controls as code (services, libraries, infrastructure-as-code, policy-as-code) for AI/ML platforms and workloads.

* Lead and help setup the basic infrastructure needed to safely rollout AI - MCPs, LLMs, pipelines, Test harness for AI (ie: harmbench), intake automation.

* Partner with data science and MLOps teams to harden:

• Data ingestion and labeling
• Training and fine-tuning pipelines
• Model registries and deployment workflows
• Inference APIs, agents, and integrations

* Define and champion secure reference architectures and patterns for common AI use cases and focus on composable architecture.

AI use case intake & governance

* Design, implement, and continuously improve the intake, triage, and review process for AI/ML and generative AI use cases across the organization.

* Build and automate self-service workflows (e.g., request forms, risk questionnaires, routing, approvals) that balance speed of delivery with security, privacy, and compliance with a focus on risk scoring and scorecards.

* Define risk-based criteria for AI use case approval, including data sensitivity, model and vendor selection, integration patterns, and control requirements; this will involve in re-mapping the complete end to end lifecycle.

* Review proposed AI solutions from concept through deployment, providing clear, actionable guidance to product and engineering teams.

* Maintain visibility into the AI use case portfolio and risk posture, and provide regular reporting to leadership and governance bodies.

Monitoring, detection & assurance

* Establish and maintain monitoring and detection for AI-specific threats, such as:

• Prompt injection and jailbreak attempts
• Data exfiltration and sensitive data exposure
• Misuse or abuse of AI tools and agents
• Anomalous model or pipeline behavior

* Integrate AI/ML systems with existing logging, SIEM, and incident response processes.

* Lead or participate in AI-focused security assessments, red-teaming, and adversarial testing; drive remediation and verification.

Strategy, leadership & enablement

* Help define and evolve the organization's AI security strategy, standards, and roadmap in partnership with Security, Engineering, Data, Legal, Privacy, and Risk.

* Translate global privacy, data sovereignty, and regulatory requirements into practical technical controls for AI workloads across multiple cloud environments.

* Prepare and deliver executive-ready briefings and narratives on AI security risks, controls, and progress.

* Mentor other engineers and serve as THE internal subject matter expert on AI/ML security, generative AI, and LLM-based systems.

Qualifications Expected for Position

• 7+ years of experience in information security, security engineering, or related fields, including significant time building and securing production systems.
• 3+ years of hands-on experience with AI/ML technologies (such as LLMs, RAG, model training/fine-tuning, MLOps, or AI-powered products), including implementation of security controls or guardrails for these systems.
• Strong programming skills in one or more relevant languages (e.g., Python, TypeScript/JavaScript, Go, or similar), with a track record of contributing to production-grade tools, services, or libraries.
• Deep understanding of cloud security architecture and controls on at least one major cloud platform (AWS, Azure, or GCP), including identity, networking, secrets management, data protection, logging, and monitoring.
• Experience designing and implementing controls in a highly regulated environment; healthcare or financial services preferred.
• Demonstrated ability to lead complex technical initiatives across multiple teams, from problem definition through design, implementation, and adoption.
• Proven ability to communicate complex technical and risk topics clearly to both engineering teams and senior leadership.

Preferred Qualifications:

* Practical experience securing LLM- and genAI-based systems, such as:

• RAG architectures backed by internal data
• AI assistants, copilots, or agents integrated with enterprise tools
• Fine-tuned models and model hosting platforms

* Experience with AI IDE tools

• cursor, windsurfer, others
• Knows the security problems and has practical solutions that balances innovation with innovation.

* Familiarity with AI/ML frameworks and ecosystems (e.g., TensorFlow, PyTorch, Scikit-learn) and/or modern LLM development stacks and IDEs (e.g., API-based LLMs, self-hosted models, AI-enhanced coding tools).

* Experience with:

• Security for data pipelines, feature stores, and model registries
• Detection engineering or SIEM tuning for AI-related events
• Red-teaming or adversarial testing of AI systems

* Evidence of ongoing engagement with AI and security (such as side projects, open-source contributions, lab environments, publications, or conference talks).

* Familiarity with emerging AI security and safety standards and forward-looking industry guidance and horizon reports.

* Relevant certifications (e.g., cloud security, security engineering, or governance) are a plus.

* Strong analytical and problem-solving skills, with the ability to operate effectively in a fast-evolving technical and regulatory landscape.

* High level of integrity and ethical conduct.

This role is a fit if you:

* Regularly build, break, or secure AI/ML or LLM-based systems in your day-to-day work or personal projects.

* Are comfortable reading and writing code, experimenting with new AI tools, and wiring them into real systems.

* Enjoy turning ambiguous AI ideas and risks into concrete architectures, controls, and automation.

* Can move fluidly between deep technical discussions and concise, executive-level explanations.

This role is not a fit if you:

* Prefer to focus solely on policy, governance, or vendor assessments without hands-on technical work.

* Do not actively engage with current AI/LLM tooling, research, and emerging practices.

* "Describe a specific LLM or AI/ML system you have secured. What were the main risks and what controls did you implement?"

* "What AI tools, libraries, or environments do you actively use or experiment with today (work or personal), and for what?"

* "What do you see as the most important AI security or safety developments on the horizon over the next few years, and why?"

The base salary range for this position is$180,000 - $190,000. In addition to a base salary, this position is eligible for a performance bonus and benefits (subject to eligibility requirements) listed here: Teladoc Health Benefits 2026.Total compensation is based on several factors including, but not limited to, type of position, location, education level, work experience, and certifications.This information is applicable for all full-time positions.

We follow a Flexible Vacation Policy, intended for rest, relaxation, and personal time. All time off must be approved by your manager prior to use. You will also receive 80 hours of Paid Sick, Safe, and Caregiver Leave annually. This applies to full-time positions only. If you are applying for a part-time role, your recruiter can provide additional details.

As part of our hiring process, we verify identity and credentials, conduct interviews (live or video), and screen for fraud or misrepresentation. Applicants who falsify information will be disqualified.

Teladoc Health will not sponsor or transfer employment work visas for this position. Applicants must be currently authorized to work in the United States without the need for visa sponsorship now or in the future.

Why join Teladoc Health?

• Teladoc Health is transforming how better health happens. Learn how when you join us in pursuit of our impactful mission.

• Chart your career path with meaningful opportunities that empower you to grow, lead, and make a difference.

• Join a multi-faceted community that celebrates each colleague's unique perspective and is focused on continually improving, each and every day.

• Contribute to an innovative culture where fresh ideas are valued as we increase access to care in new ways.

• Enjoy an inclusive benefits program centered around you and your family, with tailored programs that address your unique needs.

• Explore candidate resources with tips and tricks from Teladoc Health recruiters and learn more about our company culture by exploring #TeamTeladocHealth on LinkedIn.

As an Equal Opportunity Employer, we never have and never will discriminate against any job candidate or employee due to age, race, religion, color, ethnicity, national origin, gender, gender identity/expression, sexual orientation, membership in an employee organization, medical condition, family history, genetic information, veteran status, marital status, parental status, or pregnancy). In our innovative and inclusive workplace, we prohibit discrimination and harassment of any kind.

Teladoc Health respects your privacy and is committed to maintaining the confidentiality and security of your personal information. In furtherance of your employment relationship with Teladoc Health, we collect personal information responsibly and in accordance with applicable data privacy laws, including but not limited to, the California Consumer Privacy Act (CCPA). Personal information is defined as: Any information or set of information relating to you, including (a) all information that identifies you or could reasonably be used to identify you, and (b) all information that any applicable law treats as personal information. Teladoc Health's Notice of Privacy Practices for U.S. Employees' Personal information is available at this link.