Job Description
“We are seeking a hands-on GenAI Product E2E Technical Delivery Lead to own the full lifecycle of our Generative AI product initiatives from architecture and design through implementation, deployment, and continuous optimization. This individual will serve as the technical anchor who connects data engineering, data science, infrastructure, security, and product teams to deliver secure, scalable, and modular GenAI solutions. The ideal candidate has a proven track record of shipping production-grade GenAI products and stays at the forefront of the rapidly evolving AI landscape.
Key Responsibilities
End-to-End Delivery Ownership: Lead the complete delivery lifecycle of GenAI products, from ideation and build through production deployment, monitoring, and iteration. Translate business requirements into technical architectures and executable delivery roadmaps, ensuring on-time, high-quality outcomes.
Technical Architecture & Design: Design and oversee the implementation of end-to-end GenAI solutions, including LLM integration, retrieval-augmented generation (RAG) pipelines, agentic workflows, vector databases, orchestration frameworks, prompt engineering layers, evaluation systems, and model serving infrastructure. Ensure architectures are modular, composable, and cloud native.
Security, Scalability & Compliance: Embed security, privacy, and responsible AI principles throughout the stack including data governance, restricted data handling, prompt injection defenses, access controls, model guardrails, and auditability. Architect for horizontal scalability, cost efficiency, and resilience under production load.
Hands-On Technical Leadership: Roll up your sleeves to code, review delivery, debug production issues, and prototype new capabilities. Set technical standards, mentor engineers, and raise the bar for engineering excellence across the team.
Cross-Functional Integration: Serve as the connective tissue across data engineering, MLOps, platform, security, product, and business stakeholders. Unblock teams, resolve technical trade-offs, and drive alignment on architectural decisions.
Innovation & Technology Scouting: Stay current with the cutting edge of GenAI new foundation models, reasoning techniques, agent frameworks, fine-tuning methods, inference optimizations, and emerging standards. Evaluate and pilot new technologies and guide build-vs-buy decisions.
Operational Excellence: Establish robust CI/CD, LLMOps, observability, evaluation harnesses, A/B testing, and feedback loops for GenAI products. Define SLAs, monitor model performance drift, hallucination rates, latency, and cost-per-inference.
We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.
Required Skills & Experience
quired Qualifications
• 10+ years of software engineering experience, with 2+ years delivering production GenAI or applied ML products end-to-end
• Demonstrated hands-on experience shipping at least one GenAI product to production (LLM-powered applications, copilots, agents, RAG systems, or similar)
• Deep technical proficiency with LLM APIs and frameworks such as Anthropic Claude, OpenAI, LangChain/LangGraph, LlamaIndex, or equivalent orchestration tools
• Strong experience with vector databases and embedding models
• Expertise in at least one major cloud platform (Azure, AWS, or GCP) and its AI/ML services (Azure OpenAI, Bedrock)
• Solid grounding in software architecture patterns, microservices, API design, containerization (Docker, Kubernetes), and infrastructure-as-code
• Proficiency in Python and at least one other production language
• Experience with MLOps/LLMOps practices: model evaluation, prompt versioning, experiment tracking, monitoring, and cost optimization
• Strong understanding of AI security concerns prompt injection, data leakage, jailbreaks, model supply chain risks and mitigation strategies
• Excellent communication skills with the ability to translate complex technical concepts for both engineering and executive audiences”
Benefit packages for this role will start on the 1st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.