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UiPath Developer – Agentic AI & Maestro

About WonderBotz

WonderBotz is a global leader in intelligent automation, delivering innovative RPA and AI solutions that help organizations scale efficiently, reduce costs, and unlock new opportunities. Our team blends technical expertise with business insight to ensure clients achieve measurable success.

Role Overview

We are seeking a UiPath Developer with hands-on experience in Agentic AI and Maestro orchestration. You will design, build, and optimize automation solutions that integrate advanced AI capabilities, ensuring seamless execution across enterprise-scale environments. This role requires strong technical skills, creativity in solution design, and the ability to collaborate with cross-functional teams.

Key Responsibilities

• Develop, configure, and deploy automation workflows using UiPath Studio and Orchestrator.
• Integrate Agentic AI capabilities into RPA solutions to enable intelligent decision-making.
• Utilize Maestro for orchestration, monitoring, and scaling of automation programs.
• Collaborate with business SMEs to gather requirements and translate them into technical designs.
• Build and maintain reusable components, libraries, and frameworks for automation.
• Conduct testing, debugging, and performance tuning of automation solutions.
• Document processes, technical specifications, and best practices.
• Provide support for production deployments and ongoing maintenance.

Qualifications

• 3–5 years of hands-on UiPath development experience (Studio, Orchestrator, Robots).
• Proven expertise with Agentic AI integration in automation workflows.
• Experience with Maestro for orchestration and enterprise automation management.
• Strong understanding of RPA lifecycle (design, development, testing, deployment, support).
• Familiarity with programming languages (VB.Net, C#, Python, SQL) is a plus.
• Knowledge of AI/ML concepts, NLP, and intelligent document processing preferred.
• UiPath certifications (Developer, Advanced RPA Developer) highly desirable.

Desired Characteristics

• Strong problem-solving and analytical skills.
• Excellent communication skills for technical and non-technical stakeholders.
• Ability to work independently and in collaborative team environments.
• Detail-oriented with a focus on quality and scalability.
• Passion for innovation and continuous learning in automation and AI.

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

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

• 
  
  
• 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

• 
  
  
• 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

• 
  
  
• 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.

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.

Join Our Mission to Bridge the Digital Divide - Through AI!

Position: Programs Manager (AI Curriculum - Higher Ed) - Austin, Texas (Hybrid or Remote)

Salary Range: USD 55,000 - 75,000 annually (with a 3-month probation)

Location: Preference for Austin, Texas; remote possible

Travel: Occasional travel required with reasonable notice and accommodations

About Us

Sustainable Living Lab USA (SLL LLC USA) is part of a global movement, HQ in Singapore, offices in India, Indonesia, Japan, and the USA, to make technology inclusive, accessible, and sustainable. We design and deliver innovative education programs that equip learners with essential digital and AI skills - from US community colleges to grassroots organizations worldwide.

About the Role

We’re seeking a dynamic, articulate, and adaptable Programs Manager (AI Curriculum for HigherEd)to support the global expansion and US localization of our AI education programs.

This role involves delivery, curriculum creation, and program development, ideal for someone confident in discussing AI with non-technical audiences, passionate about learning, and eager to influence AI upskilling’s future. You’ll lead technical Train-the-Trainer (TTT) sessions with professors from community colleges and universities both virtually and in-person helping them develop/integrate technical AI concepts as part of their certifications/degrees.

This role blends delivery, curriculum design, and program development, ideal for a flexible, self-motivated individual with a growth mindset who thrives in ambiguous environments, constantly finding solutions to new problems.

Key Responsibilities

1. AI Programs Training & Facilitation (TTT Model)

• Lead virtual and in-person technical Train-the-Trainer (TTT) workshops across US, supporting partners in vocational education and workforce institutions worldwide.
• Ensure participants understand the content and are equipped to customize it for local contexts and learner needs.
• Develop and implement standardized training regimens and SOPs tailored for cross-cultural, regional, and state-wide implementation partners.
• Translate core AI, ML, DL, and Python concepts into engaging, beginner-friendly lessons sensitive to language diversity and digital fluency levels - but also able to deliver technical concepts like Maths for AI, Data science, and Agentic AI topics in depth.
• Conduct engaging and informative training sessions utilizing a standardized curriculum.

2. US Programme & Business Development (SMEs, Colleges, Universities, K12, communities)

• Manage the continuity and expansion of SLL's US programs, particularly within its extensive network of 140+ community colleges and universities spanning 40+ states.
• Work with the team to position SL2 as a leading partner in AI and emerging tech education for the US community college and vocational sector.
• Scale educational programs with school districts, community colleges, and universities, focusing on out-of-school programs and boot camps.
• Scale AI Community Engagements with clubs, societies, and foundations.
• Identify and articulate compelling use-case stories for workforce development partnerships.
• Support engagements with colleges, government agencies, and employers to co-develop bespoke AI education pathways.

3. Content Development and Productization

• Collaborate with internal teams to evolve and update existing programs and co-create new offerings.
• Lead the creation of slide decks, training decks, and other content as a core part of the role.
• Contribute to productizing key experiential learning offerings such as hands-on coding challenges and platform-based simulated work experiences.
• Help localize material for US-based institutions, aligning with skills frameworks and employer demand.
• Co-deliver experiential coding/skilling events, ensuring the core product is designed for global scalability and is adaptable to various educational levels, including tailoring project focus for different competitions for community college and university students.

What We're Looking For

• HigherEd/SME Training Experience: Minimum of 3 years in Higher Ed, training, or facilitation working with HigherEd/SMEs, including at least 2 years focused on technical or digital skills. Experience working across cultures and time zones is highly valued.
• Tech & Learning Aptitude: Intermediate to high knowledge of Python and AI/ML/DL/Agentic AI/Maths for AI/Data concepts. Strong personal interest in the evolving AI landscape and comfort with explaining complex topics to beginners. Experience or enthusiasm for Vibe Coding, digital hackathons, or collaborative prototyping is a plus.
• Communication & Facilitation: Fluent, clear-spoken English and strong public speaking skills. Able to adjust tone, pace, and clarity based on audience (e.g., teachers vs. college professors vs. workforce leaders). A strong presence on MS Teams/Zoom or in person - whether running a classroom session, hackathon, or partner presentation.
• Mindset & Tools: Adaptable, self-motivated, and collaborative. Skilled in using tools like Zoom, Google Workspace, and Teams, and eager to learn new platforms and facilitation techniques.
• Location & Eligibility: Preference for candidates based in Austin, TX, but open to strong remote applicants. Must be authorized to work in the US.

Why Join Us?

• Make Global Impact: Empower teachers and workforce educators across continents to teach AI confidently and contextually.
• Shape the Future of the US Workforce Skilling: Co-create impactful AI programmes for colleges and workforce partners across the US.
• Creative & Collaborative Culture: Work with a mission-driven team that values experimentation, equity, and lifelong learning.
• Featured Benefits: Medical insurance (100% employer contribution), 14 days annual leave, 14 days medical leave, and paternity and maternity leave. We request that the candidate to have their own device.

Ready to Apply?

Send your resume and a short, authentic cover letter to with the subject line: “Programs Manager (AI Curriculum) - U.S.” Please write authentically, and use AI tools with discernment.

Please include:

• Your expected monthly salary in USD
• Your current location and time zone
• Your availability to start
• Any accommodation requests (if applicable)

SLL LLC USA is an Equal Opportunity Employer. We celebrate diversity and are committed to building an inclusive workplace. If you need accommodations during the application process, please let us know.

GENERAL SUMMARY:

The Manager of AI Enablement (Senior) leads the development and execution of Element Care’s internal approach to artificial intelligence. This role defines AI standards, policies, and best practices while enabling staff across the organization to adopt AI safely, ethically, and effectively. Reporting to the IT department, this position acts as a trusted advisor to leaders and end users, shaping AI governance, vendor strategy, training, and enterprise enablement.

ESSENTIAL RESPONSIBILITIES:

•    Define and maintain organizational AI standards, policies, and governance frameworks.

•    Lead the deployment of off-the-shelf AI solutions, including ambient documentation, predictive analytics, administrative automation, and clinical decision support tools.

•    Enable responsible use of generative AI across administrative and operational functions.

•    Conduct continuous workflow analysis to identify automation and AI-enablement opportunities.

•    Evaluate AI and AI/ML models, tools, and vendor solutions for suitability, risk, and value.

•    Partner with IT, data, analytics, and platform teams to align AI initiatives with enterprise architecture.

•    Provide oversight and guidance on AI-enabled workflows, automation, and agent capabilities.

•    Measure, monitor, and report on AI initiative outcomes, value realization, and performance.

•    Build business cases and recommendations for future AI investments.

•    Serve as the primary advisor to leaders and teams on AI use cases, risks, and governance.

•    Monitor regulatory, ethical, and industry developments related to AI.

•    Help establish and mature a scalable AI enablement and governance operating model.

•    Influence adoption and consistency without direct authority.

•    Perform other duties as assigned.

JOB SPECIFICATION:

•    6–10+ years of relevant professional experience, including applied AI, automation, analytics, or emerging technology leadership.

•    Demonstrated experience evaluating AI/ML models, vendor solutions, or AI platforms.

•    Experience with vendor management, solution selection, or hands-on implementation required.

•    Demonstrated experience defining standards, policies, or enterprise enablement programs.

•    Healthcare or other regulated industry experience strongly preferred.

•    Strong understanding of applied AI, AI/ML evaluation, governance, risk, and ethical considerations.

•    Ability to translate complex concepts into practical organizational guidance.

•    Experience developing business cases and value narratives for technology investments.

•    Executive-level communication and facilitation skills.

•    Proven ability to operate independently and influence across the enterprise.

•    Strategic mindset with a pragmatic, implementation-oriented approach.

Compensation details: 13 Yearly Salary

PI71b2d5685c13-3631

Role: Principal AI Solution Architect

Location: Houston, TX, 77086 - Onsite

Duration: Long term Contract

Job Description:

Key Responsibilities:

• Partner with business and technical stakeholders to identify and implement agentic AI and machine learning solutions that improve decision making, workflows, and automation
• Design and implement cloud native AI architectures using Microsoft Azure services and established AI design patterns
• Collaborate with Data Scientists and other AI Engineers to transform prototypes into production ready, scalable solutions
• Build, deploy, and operate enterprise scale machine learning pipelines, emphasizing reliability, performance, and security
• Orchestrate and configure infrastructure that enables low latency, resilient AI workloads, leveraging infrastructure as code and automation
• Contribute to reusable accelerators, templates, and patterns that improve delivery speed and consistency across teams
• Support CI/CD, monitoring, and operational practices for AI and ML systems in production environments

Required Technical Skills:

• Strong experience with Microsoft Azure, including AI/ML services and cloud native architectures
• Hands on experience deploying and operating ML pipelines using Azure Machine Learning
• Proficiency in Python and modern software engineering practices
• Experience with automation and configuration management, including Ansible
• Solid understanding of MLOps, model lifecycle management, and CI/CD for AI systems
• Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes)
• Working knowledge of security, identity, and access control in enterprise cloud environments

Preferred Skills:

• Experience with Microsoft Foundry
• Experience implementing or operating agentic AI systems
• Familiarity with data engineering tools such as Databricks, Spark, Azure Data Factory
• Experience integrating AI services (e.g., cognitive services, computer vision, unstructured data processing)

Experience Requirements:

• 5+ years of experience in software engineering, AI engineering, or machine learning engineering roles
• Proven experience delivering production AI or ML solutions in a cloud environment
• Experience collaborating with cross functional teams across data science, engineering, and architecture

Ways of Working:

• Ability to work independently as a contractor while integrating effectively with existing teams
• Strong communication skills, with the ability to explain complex technical concepts clearly
• Results oriented mindset with a focus on delivering business value quickly and reliably.

We are looking for a Generative AI Lead to drive the design and delivery of advanced AI solutions for enterprise clients.

This role sits at the intersection of hands-on engineering, system architecture, and technical leadership, focused on building production-grade GenAI systems that solve complex, real-world business problems.

What You’ll Do

• Lead the design and development of enterprise-scale Generative AI solutions
• Architect and implement multi-agent AI systems and retrieval-augmented generation (RAG) pipelines
• Integrate LLM capabilities into business workflows and enterprise applications
• Partner with business stakeholders to translate complex problems into scalable AI solutions
• Guide and mentor engineering teams while maintaining a high bar for technical quality
• Ensure reliable deployment, monitoring, and performance of AI systems (including handling hallucinations, drift, and scaling challenges)
• Optimize infrastructure across cloud environments, including compute and GPU utilization

What We’re Looking For

• Proven experience building and deploying LLM-based / Generative AI applications in production
• Strong hands-on expertise in Python and modern AI frameworks (e.g., LangChain, LlamaIndex)
• Experience designing RAG pipelines, semantic search systems, or knowledge retrieval architectures
• Exposure to multi-agent frameworks (e.g., LangGraph, CrewAI) or similar architectures
• Experience working in cloud environments (AWS, Azure, or GCP) and scaling AI systems
• Demonstrated ability to lead technical teams or initiatives
• Strong communication skills with the ability to collaborate with both technical and business stakeholders

Nice to Have

• Experience working in regulated industries (e.g., healthcare, life sciences, financial services)
• Familiarity with vector databases (e.g., Pinecone, Weaviate)
• Background in enterprise AI platform development or data infrastructure

Why This Role

• Opportunity to build real-world GenAI systems at scale (not just prototypes)
• Own end-to-end architecture and delivery, from concept to production
• Work on high-impact use cases across enterprise clients
• Collaborate with cross-functional teams across engineering, product, and business

About MathCo

MathCo is a global Enterprise AI and Analytics company helping Fortune 500 organizations solve complex business problems through data and AI. Our work spans advanced analytics, AI platforms, and scalable solutions that deliver measurable business impact.

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.