Profound Ai Tool Jobs in Usa

Job Summary
HellermannTyton North America (HT NA) is accelerating the use of Artificial Intelligence to unlock capacity, improve quality, and fuel growth across North America. As the AI Program Manager, you will build and run a program of AI initiatives that create efficiencies by automating repetitive tasks and removing process waste. You will partner with Operations, Sales, Marketing, IT, HR, and Finance to select the right problems, deliver measurable outcomes quickly, and scale wins across plant sites to increase revenue, reduce cost, and eliminate waste. This will be achieved while maintaining HellermannTyton's Quality and EHS certifications by supporting all corporate policies, procedures, work instructions, and required documentation.

What You'll Do

Opportunity Discovery

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• Conduct stakeholder interviews to capture business objectives and constraints; translate high-level goals into clear, actionable AI project requirements.
  
  
• Build simple business cases with the respective departments; baseline current performance, and quantify benefits
  
  

Program Management

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• Work with Business Stakeholders to prioritize initiatives by value, impact, labor hour avoidance, and risk mitigation.
  
  
• Prioritize AI program and project roadmap into short, iterative deliverables; prioritize delivery based on business impact and feasibility.
  
  
• Run stage-gated delivery (scope pilot scale) aligned to HellermannTyton COE project governance; set decision forums, risk controls, and incremental results.
  
  
• Work with Business and IT to develop data and IT infrastructure and tools to support AI program roadmap.
  
  

Delivery

• 
  
  
• Ensure ownership of agents and AI workflows are transitioned to business stakeholders within the business.
  
  
• Engage with change management to ensure AI projects are accepted, and AI becomes integrated into processes such that AI becomes "the way we work."
  
  
• Make value visible and auditable. Track and report on program benefit metrics such as savings, improved experience, reduced waste, efficiency improvements, etc.
  
  
• Share AI knowledge to upskill the organization. Coach stakeholders to see AI use cases in the processes.
  
  

Governance

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• Partner with Legal/HR on data privacy and AI use policies.
  
  
• Ensure solutions comply with IT corporate cybersecurity and risk guidelines.
  
  

Success in this role will require:

• 
  
  
• Collaboration & Communication
  
  
• Adaptability
  
  
• Problem Solving
  
  
• Analytical Thinking
  
  
• Business Acumen
  
  

What You'll Bring

• 
  
  
• Bachelor's degree in Project/Program Management, Engineering, Manufacturing, Computer Science, Data/Analytics, or related field.
  
  
• 3+ years leading data/AI/automation programs with manufacturing operations; proven track record delivering hard dollar benefits and labor hour avoidance.
  
  
• Mastery of program management (business cases, roadmaps, stage gates, financials).
  
  
• Excellent stakeholder communication and leadership across Operations, Sales, Marketing, IT, HR, and Finance.
  
  

Preferred Qualifications

• 
  
  
• Background manufacturing or associated environments.
  
  
• Lean / Six Sigma certification; experience embedding AI within continuous improvement programs.
  
  
• Experience with AI Tools (MS CoPilot Studio, MS Fabric, MS Azure Foundry)
  
  

By applying for a position with HellermannTyton, you understand that should you be made an offer, it will be contingent on your undergoing and successfully completing a background check through the use of our 3rd party supplier. Background checks may include some or all of the following based on the nature of the position: SSN/SIN validation, education verification, employment verification, criminal check, driving history, and drug test. You will be notified during the hiring process of which checks are required by the position.

HellermannTyton Corporation is an Equal Opportunity Employer and does not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state or local protected class.

AI Strategist

Senior Director, Consulting & Delivery

Level & Department

The honest version of what's happening in enterprise AI in the middle market ($100M - $2B) right now is messy. Most organizations know they need to move. Very few have the leadership that can operate fluently at both ends of the problem… the C-suite conversation about investment rationale and the engineering conversation about whether the architecture can actually support what was just promised.

That gap is expensive and we've seen it in every sector we work in. It shows up the same way every time: smart strategy work that doesn't connect to anything deployable, or capable technical teams building things that never get funded or adopted.

The Principal AI Strategist role exists to close that gap on our most important engagements.

THE ROLE

What this position actually does

You are the senior-most strategy and delivery mind on a client engagement. You hold the intellectual and commercial thread across the entire lifecycle from the first diagnostic conversation through to a working AI system in production and the expansion that follows when the client realizes it's changing something real.

You are not the person who manages the team to do the thinking… you are responsible for the most strategic form of that thinking. You shape the strategy, challenge the architecture, own the executive relationship, and are personally accountable for whether the engagement creates measurable business value.

The title is Principal AI Strategist because that's the actual job. The level is Senior Director because that reflects the scope, accountability, and authority this role carries inside Quantum Rise and in front of clients.

OUR OPERATING PRINCIPLES

The intellectual framework you'll work inside

Quantum Rise operates from a set of principles we call Consulting 2.0. They define how engagements are structured, how we challenge client assumptions, and what we hold ourselves accountable to.

Think like an investor, not a technologist

AI value is relative to each client’s own goals / circumstances and capital is precious. We anchor every engagement to strategy → value streams → enterprise value. We don't start with use cases. We start with where the business makes and loses money, and work backward to where AI creates leverage.

• Map to where the work actually happens: We go to L4–L5 process depth where the task-level execution that explains KPI performance and reveals where AI readiness actually exists.
• Diagnose before prescribing: We use structured diagnostic lenses (process, data, systems) to move from visible symptoms to root causes.
• Data reality bounds AI ambition: What AI can reliably do is determined by the strength of the data foundation (architecture, integration, quality, consumption) not by model choice.
• Not all AI systems are created equal: Machine learning, LLMs, and agents introduce different capabilities, constraints, and operational trade-offs. Enterprise-ready agents specifically require probabilistic reasoning balanced with deterministic rules, structure, guardrails, and human oversight.
• Risk is predictable: Enterprise AI risk falls into defined categories: data privacy, bias, explainability, and governance. Principles define what good looks like; governance establishes ownership, decision rights, and escalation.
• Execution credibility matters as much as technical ambition: “Crawl”and MVP solutions that are in production beat “Run” enterprise-wide solutions that aren't.

RESPONSIBILITIES

What you own

Client strategy and delivery

• Lead end-to-end engagement execution from strategy and diagnostic through deployment and commercial expansion
• Run executive discovery sessions translating ambiguous business problems into structured AI investment rationales
• Build the business case with the rigor of an investor, not the optimism of a vendor: quantified value, honest constraints, sequenced roadmap
• Own the relationship with C-suite and senior client stakeholders as a peer, not a service provider

Technical leadership

• Apply working fluency in LLMs, agentic workflows, RAG architecture, and data infrastructure to make real design decisions ensuring the original business value is obtained
• Collaborate with engineering to challenge, refine, and pressure-test solutions against production realities
• Define AI product roadmaps that are incrementally value generating, governed, measured, and adopted

Firm development

• Identify capability and offering gaps where Quantum Rise can build durable competitive advantage
• Build reusable delivery IP (frameworks, playbooks, diagnostic tools) that improve every engagement that follows
• Develop and mentor the next generation of AI consultants on what it means to operate at the intersection of AI strategy and delivery
• Contribute to business development through the quality of your work and the depth of your client relationships

THE PROFILE

Who fits here

person who thrives in this role has a particular combination that's genuinely rare and we'd rather name it honestly than let both sides waste time discovering the mismatch.

Dimension: What this looks like in practice

Role identity: You think of yourself as a strategist who builds things, not a consultant who advises on them.

Technical depth: Hands-on with LLMs and agentic coding. You've debugged a pipeline at some point and don't need to be reminded why hallucination is an enterprise risk.

Business fluency: You can translate AI capability into a CFO-ready investment case without losing the technical precision that makes it credible.

Delivery record: 12+ years in management consulting or technical advisory with real end-to-end accountability from scoping through go-live. You are hyper customer service oriented.

Sector context: You have meaningfully operated across 3 discrete sectors learning to how effectively understand how money is actually made, customer and demand dynamics, how work gets done, regulatory constraints, etc.

Education: Engineering, CS, or MIS undergraduate foundation. MBA preferred. The combination matters and what makes the translation instinct natural. What matters is the ability to translate value creation into technology and vice versa.

Working style: You reach for the AI tool first because it's genuinely how you think and not just because we’re an AI consultancy.

BENEFITS

What we offer

• Competitive base salary + variable compensation tied to individual and company performance
• Equity options
• BCBS health, vision, and dental
• 401(k) with discretionary annual match
• FSA, DCA, commuter, and L&D stipends
• Unlimited PTO + paid holidays + paid sick time

AI & Business Systems Manager

Christopher Homes, a nationally acclaimed luxury residential developer and home builder, has been creating Nevada’s finest neighborhoods since 1981. Within four decades, we have developed over 2,000 homes with a total value of over $1 Billion.

Our experience and reputation for developing luxury residential neighborhoods is unmatched. Of note, Christopher Homes has been awarded over 150 national and local awards for design excellence, which include: 19 Home of the Year awards, 7 Community of The Year awards, and recognized as the Homebuilder of the Year by the National Association of Homebuilders (NAHB), and numerous other awards.

Our Purpose



Enhancing lives by creating innovative homes and communities that inspire and reflect the unique interests of our residents. How we do anything is how we do everything. We are creators. The foundation of our success is rooted in our culture and our most valuable resource is our people. We are a diverse group made up of smart, creative, and dedicated people that are passionate about transforming the modern living experience.

Position Overview

The AI & Business Systems Manager is a senior, hands-on role responsible for designing, governing, and operationalizing artificial intelligence across Christopher Homes’ real estate development and luxury homebuilding platform. The manager will report to our CFO. This role requires deep, proven experience in real estate development and residential construction combined with advanced applied AI, data, and enterprise systems expertise.

The manager can work on-site or have a hybrid schedule.

This individual will lead the transformation of fragmented data and disconnected systems into a clean, structured, AI-ready ecosystem that improves efficiency, reduces costs, enhances forecasting, and elevates the customer experience. This is not a research role—this position focuses on practical, secure, ROI-driven AI embedded directly into daily workflows.

This is a full-time, individual contributor role with enterprise-wide responsibility and visibility.

Key Responsibilities

AI STRATEGY & IMPLEMENTATION (PRIMARY FOCUS)

·      Design and execute an enterprise AI roadmap aligned with real estate development and homebuilding workflows

·      Embed AI directly into core systems including Procore, ERP, Buildtopia, HubSpot, and Microsoft platforms

·      Identify and deploy AI use cases for:

–        Cost control and variance detection

–        Schedule and cycle-time optimization

–        Purchasing and vendor analysis

–        Warranty trend prediction and root-cause analysis

–        Marketing performance and lead intelligence

·      Automate repetitive, manual, and error-prone processes using AI and intelligent workflows

·      Ensure all AI solutions are secure, compliant, and aligned with data privacy best practices

DATA ARCHITECTURE, CLEANUP & GOVERNANCE

·      Assess, clean, normalize, and structure data across all business systems

·      Establish data standards, naming conventions, and governance policies

·      Eliminate duplication, silos, and inconsistent data definitions

·      Ensure data integrity to support reliable AI-driven insights and decision-making

·      Prepare data architecture to support future scalability and AI maturity

REAL ESTATE DEVELOPMENT & CONSTRUCTION SYSTEMS LEADERSHIP

Serve as the internal expert on how AI supports:

              – Land development

            – Vertical construction

-- Purchasing and contracts

            – Design center operations

            – Warranty and post-close service

·      Deeply understand how data flows through real estate development and homebuilding lifecycles

·      Optimize system usage to reflect how the business actually operates—not generic software assumptions

·      Partner with vendors, consultants, and software providers during system enhancements or ERP transitions

BUSINESS PARTNERSHIP & CHANGE MANAGEMENT

·      Translate real estate development and construction challenges into AI-enabled solutions

·      Partner closely with executive leadership and department heads

·      Educate teams on AI tools, best practices, and responsible usage

·      Adoption of AI-enabled workflows across the organization

REPORTING, FORECASTING & DECISION INTELLIGENCE

·      Build AI-powered dashboards, reports, and forecasting tools

·      Improve visibility into costs, schedules, risks, and performance

·      Enable leadership to make faster, more accurate, data-driven decisions

REQUIRED QUALIFICATIONS   

·      8+ years of experience in real estate development, residential construction, or homebuilding environments

·      Demonstrated, hands-on experience applying AI to real business systems

·      Deep understanding of development and construction workflows, terminology, and financial drivers

·      Proven ability to organize, clean, and govern complex operational and financial data

·      Experience with enterprise systems such as:

            – Procore

            – ERP systems (Sage 100 Contractor or similar)

             – Buildtopia (Purchasing, Design Center, Construction and Warranty)

            – CRM & Marketing platforms

            – Microsoft ecosystem (including Copilot)

·      Strong understanding of data security, privacy, and compliance in business environments

·      Ability to operate independently and drive outcomes without direct supervision

STRONGLY PREFERRED

·      Luxury single-family or for-rent residential development experience

·      Experience leading ERP transitions or system integrations

·      Applied knowledge of predictive analytics and automation in construction

·      Ability to communicate complex technical concepts to non-technical stakeholders

IDEAL CANDIDATE PROFILE

·      Deeply grounded in real estate development and construction

·      Business-first mindset with strong technical execution

·      Focused on measurable ROI, efficiency, and cost savings

·      Disciplined, pragmatic, and trustworthy with sensitive data

·      Comfortable building foundational systems before scaling AI initiatives

Senior Business Analyst Life & Annuities

Onsite in WDM office 4 days a week

Contract

Overview:

We are seeking an experienced Senior Business Systems Analyst (AI Enablement) to support ***'s AI transformation initiatives. This role will partner with ***'s BSA team, IT leadership, and PMO to understand current SDLC processes, identify pain points, gaps, and inconsistencies across teams, and translate findings into a more streamlined, AI-enabled operating model.

The BSA will assess our current requirements elicitation process and help define how an AI-infused approach can significantly improve the thoroughness, completeness, and quality of user requirements specifically for consumption by an AI coding agent. This includes identifying cross-system dependencies, non-functional requirements, and user personas from initial requirement elicitation through Jira story creation. This role will help transform our BSA capabilities by leveraging custom-built AI solutions to accelerate cycle time, improve consistency, and reduce downstream rework.

This role will also define measurable success criteria and develop metrics to evaluate process improvements and AI impact across the SDLC: gathering requirements across several other SDLC-related AI initiatives and provide light project management support across multiple AI workstreams.

Key Responsibilities

Assess current BA workflows, documentation standards, and impact analysis processes from user requirement elicitation through Jira story creation, identifying gaps, redundancies, inconsistencies and improvements across teams.

Identify friction points and define AI-enabled use cases with measurable business outcomes.

Drive feedback loops for AI proofs of concept (POCs) delivered to teams by gathering structured user input, measuring adoption and effectiveness, and incorporating insights into iterative improvements.

Develop clear, actionable requirements including user stories, acceptance criteria, non-functional requirements, personas, and upstream/downstream system impacts.

Determine and help establish processes or patterns to ensure user requirements align with current system capabilities. Proactively identify cross-system dependencies, technical constraints, gaps, and system limitations in collaboration with engineering teams to ensure requirements are technically feasible and implementation-ready.

Support backlog grooming, sprint planning, demos, and pilot validation sessions.

Track progress across multiple AI initiatives, manage dependencies and risks, and maintain clear stakeholder communication.

Develop and maintain lightweight project plans, timelines, and status reporting to ensure AI initiatives remain aligned with business priorities and strategic objectives.

Required Qualifications

5+ years of Business Analysis or Business Systems Analysis experience in technology or software environments.

Strong requirements elicitation, documentation, and facilitation skills.

Experience working in Agile environments with cross-functional teams.

Practical familiarity with AI tools (e.g., Claude Code CLI, ChatGPT, Copilot) and understanding of AI concepts (LLMs, prompt engineering, AI governance, and AI risk considerations).

Strong systems thinking, structured communication, and stakeholder management skills.

Preferred Experience

Experience implementing AI or automation solutions within enterprise environments.

Familiarity with AWS AI services (e.g., AWS Bedrock) or other enterprise AI platforms.

Familiarity with Jira, Confluence, GitHub, or similar SDLC ecosystems.

Experience supporting PMO processes or managing multiple concurrent initiatives along with a functional understanding of Agile practices.

Financial services or insurance industry experience.

Success Measures

Successful delivery of an AI-enabled solution for ***'s BSA team.

Improved BA workflow efficiency, quality, and consistency.

High-quality, implementation-ready requirements that reduce downstream rework and delivery thrash.

Effective coordination, transparency, and measurable progress across AI initiatives.

Voxology is redefining patient engagement with AI-driven solutions designed to streamline healthcare access and administrative processes. Our mission is to enable healthcare providers to deliver effortless, patient-centric experiences.

Through advanced conversational AI, we power seamless communication across voice, text, and chat—reducing wait times, improving access, and enhancing the overall patient experience. By integrating with leading EMRs, we simplify the end-to-end patient journey, from scheduling and intake to financial clearance and follow-up, allowing providers to focus on delivering exceptional care.

We’re looking for a healthcare front office professional to help improve the quality and accuracy of AI-driven patient interactions.

This is a part-time (5–10 hrs/week), remote role where you’ll review real patient calls, identify issues, and help refine how AI agents handle scheduling, intake, and patient communication.

If you’ve worked at a front desk, call center, or in patient access, this is a great opportunity to get exposure to AI while leveraging your real-world experience.

• Listen to recorded patient calls and review transcripts
• Identify issues in conversations (missed scheduling opportunities, incorrect responses, confusing workflows)
• Provide clear, actionable feedback on what should have happened instead
• Tag and label conversations (patient intent, outcomes, error types)
• Ensure AI workflows align with real-world front office processes
• Identify patterns and recurring issues across interactions

• 1+ year experience in a healthcare front office role, such as:
• Patient Access Representative
• Medical Receptionist
• Scheduling Coordinator
• Healthcare Call Center Agent
• Strong attention to detail
• Comfortable reviewing calls/transcripts and providing structured feedback
• Understand how real patient conversations and workflows operate

• Experience with EMRs (Athena, NextGen, Epic, etc.)
• Exposure to scheduling, insurance verification, or referral workflows
• Prior QA, auditing, or call review experience

• Work on real-world AI used by healthcare providers
• Directly impact patient experience and access to care
• Flexible, part-time schedule
• Strong entry point into healthcare + AI

• Location: Remote
• Time Commitment: 5–10 hours per week
• Compensation: $20–$40/hour (based on experience)

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.

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.

Location: Anywhere in Country

At EY, we’re all in to shape your future with confidence.

We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.

AI & Data - AI Strategy - Senior Manager - Oil & Gas Sector

As part of our growing AI & Data practice, we are seeking a highly experienced Senior Manager to lead enterprise AI strategy and quantitative modeling efforts for our clients in the Oil & Gas sector. This individual will bring deep industry expertise, along with a proven track record of designing and operationalizing responsible, scalable, and value-aligned AI solutions. You’ll lead high-impact client engagements focused on Generative AI, Agentic AI, MLOps, and AI governance frameworks — driving measurable outcomes in upstream, midstream, and downstream operations.

As a Senior Manager in AI Strategy, you will leverage proprietary, industry-aligned business models and innovative operating model designs to deliver impactful AI investments. You will be responsible for capability assessments, operating model design, product management, governance, and process design, ensuring that AI initiatives align with business strategies and stakeholder needs.

In this role, you will lead the delivery of complex AI strategies that enhance business effectiveness and efficiency. You will work closely with clients to envision how AI can transform their markets, products, and capabilities. This position offers the opportunity to engage with business and technology leaders, driving strategic programs that significantly impact their operations.

• 
  
• Lead engagement delivery, ensuring quality and risk management throughout the project lifecycle.
  
• Manage client relationships, focusing on revenue generation and the identification of new opportunities.
  
• Develop and manage resource plans and budgets for engagements, ensuring alignment with performance objectives.
  
• Define and implement enterprise-wide AI and quantitative modeling strategy tailored to oil & gas value chains (e.g., asset optimization, drilling, trading, predictive maintenance).
  
• Establish AI governance frameworks that ensure responsible AI adoption, ethical use of data, model risk management, and alignment with evolving regulations.
  
• Design and operationalize Agentic AI solutions to automate reasoning, planning, and decision‑making tasks in complex environments.
  
• Drive the prioritization of AI use cases based on business value, feasibility, and risk, ensuring ROI on AI initiatives.
  
• Lead multidisciplinary teams of data scientists, engineers, and consultants to deliver end‑to‑end AI platforms and solutions.
  
• Partner with senior business and IT leaders to identify strategic opportunities and shape AI‑enabled business transformation.
  
• Implement and scale ModelOps and MLOps practices, ensuring transparency, reproducibility, and monitoring of models in production.
  
• Lead AI solution architecture, including hybrid deployments on cloud (e.g. Microsoft Azure, Amazon AWS).
  
• Serve as a thought leader in emerging AI technologies, including Generative AI, foundation models, RAG and Agentic AI.
  
• Drive internal capability building and innovation in Responsible AI, agentic workflows, and energy sector‑specific solutions.
  

To excel in this role, you will need a blend of technical and interpersonal skills. Your ability to navigate complex challenges and deliver innovative solutions will be crucial.

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• Strong analytical and decision‑making skills to develop solutions to complex problems.
  
• Proven experience in managing client relationships and leading teams.
  
• Ability to communicate effectively and influence stakeholders at all levels.
  

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• Bachelor’s degree required; Master’s degree preferred with focus in Computer Science, Applied Math, or related field with prior consulting experience required.
  
• 10+ years of experience in technology consulting, digital transformation, or AI‑driven business solutions.
  
• 5+ years of leadership in AI/ML projects, including team management and executive stakeholder engagement.
  
• Typically, no less than 5 — 7 years of relevant experience.
  
• Strong expertise in AI Platforms and Tools.
  
• Proficiency in Data Architecture Design and Modelling.
  
• Experience in Digital Transformation and IT Effectiveness Assessment.
  
• Knowledge of Emerging Technologies and Technology Strategy, Vision, and Roadmap.
  
• Ability to build and manage relationships effectively.
  
• Strong exposure to oil & gas industry operations, value levers, and use case landscape.
  
• Proven success in developing AI strategy and governance models, including frameworks for Responsible AI, risk, and compliance.
  
• Hands‑on experience with Generative AI frameworks (e.g., OpenAI, Hugging Face, LangChain, RAG).
  
• Experience architecting and scaling MLOps platforms and data science workflows in cloud‑native environments.
  
• Proficiency in Python and tools like Pandas, PyTorch, Scikit‑learn, Spark, SQL.
  
• Experience with CI/CD, containerization (e.g., Docker, Kubernetes), and MLFlow or similar tools.
  
• Strong client‑facing skills with the ability to articulate technical topics to business executives.
  

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• Experience in managing change and leading teams.
  
• Strong negotiation and influencing skills.
  
• Familiarity with sector knowledge and commercial acumen.
  
• Prior experience leading AI initiatives in the energy or oil & gas sector, including exploration, refining, or energy trading.
  
• Familiarity with agentic AI concepts, cognitive architectures, and autonomous agents.
  
• Working knowledge of ESG data, climate risk modeling, and regulatory trends in energy.
  
• AI certifications (Microsoft, AWS, NVIDIA, Databricks, or equivalent).
  
• Exposure to agile delivery models and design thinking approaches.
  

We seek individuals who are not only skilled but also passionate about driving innovation and transformation through AI. Top performers are those who can think critically, solve complex problems, and communicate effectively with diverse stakeholders. If you are eager to make a significant impact and thrive in a collaborative environment, we want to hear from you!

At EY, we’ll develop you with future‑focused skills and equip you with world‑class experiences. We’ll empower you in a flexible environment, and fuel you and your extraordinary talents in a diverse and inclusive culture of globally connected teams. Learn more.

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  We offer a comprehensive compensation and benefits package where you’ll be rewarded based on your performance and recognized for the value you bring to the business. The base salary range for this job in all geographic locations in the US is $144,000 to $329,100. The base salary range for New York City Metro Area, Washington State and California (excluding Sacramento) is $172,800 to $374,000. Individual salaries within those ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography. In addition, our Total Rewards package includes medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options.

  
  
  
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  Join us in our team‑led and leader‑enabled hybrid model. Our expectation is for most people in external, client‑serving roles to work together in person 40‑60% of the time over the course of an engagement, project or year.

  
  
  
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  Under our flexible vacation policy, you’ll decide how much vacation time you need based on your own personal circumstances. You’ll also be granted time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well‑being.

  
  
  

Are you ready to shape your future with confidence? Apply today.

EY accepts applications for this position on an on‑going basis.

For those living in California, please click here for additional information.

EY focuses on high‑ethical standards and integrity among its employees and expects all candidates to demonstrate these qualities.

EY provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, genetic information, national origin, protected veteran status, disability status, or any other legally protected basis, including arrest and conviction records, in accordance with applicable law.

EY is committed to providing reasonable accommodation to qualified individuals with disabilities including veterans with disabilities. If you have a disability and either need assistance applying online or need to request an accommodation during any part of the application process, please call 1‑800‑EY‑HELP3, select Option 2 for candidate related inquiries, then select Option 1 for candidate queries and finally select Option 2 for candidates with an inquiry which will route you to EY’s Talent Shared Services Team (TSS) or email the TSS at .

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