Lead AI Engineer​/Technical Project Manager

We’re looking for a hands‑on AI builder who can also run the project: partner with business stakeholders to shape requirements, rapidly build proofs of concept (PoCs), and then lead an engineering team to productionalize secure, scalable AI applications.

This is a player/coach role: you’ll be coding, reviewing, and architecting, while also driving scope, timelines, and stakeholder alignment.

• Lead workshops with business teams to clarify use cases, success metrics, data sources, risks, and constraints.
• Translate business needs into clear user stories, acceptance criteria, and delivery plans.
• Own client and stakeholder communication, status updates, and risk management.

• Build rapid AI PoCs using modern AI‑assisted development workflows.
• Evaluate and select appropriate approaches: LLMs, RAG, agents, classical ML, OCR, or non‑AI solutions when appropriate.
• Demonstrate prototypes and iterate quickly based on feedback.

• Design and implement AI applications including prompt design, retrieval pipelines, tool/function calling, and evaluation frameworks.
• Implement guardrails for reliability, security, cost control, and observability.

• Lead solutions from pilot to production including CI/CD, environments, secrets, logging, monitoring, and runbooks.
• Ensure solutions meet enterprise standards for scalability, performance, and security.
• Mentor engineers, conduct code reviews, and establish reusable patterns and templates.
• Coordinate work across frontend, backend, Dev Ops, and business SMEs.

• 5+ years of professional software engineering experience.
• Proven experience delivering AI/ML or LLM‑based solutions beyond demo stage.
• Strong ability to translate business requirements into technical solutions and delivery plans.
• Familiarity with APIs, data pipelines, and integrating AI services into applications.

• Cloud experience (Azure preferred).
• Experience with RAG, vector databases, document ingestion, and OCR.
• Experience leading or mentoring a small engineering team.

• Large Language Models (LLMs), embeddings, RAG, agents, OCR, ML frameworks.
• AI‑assisted development tools and modern IDEs.
• Cloud‑native services, CI/CD pipelines, monitoring, and logging tools.

• 30 days:
  Deliver 1–2 working PoCs with clear success metrics and a production roadmap.
• 60 days:
  Harden a selected PoC into a secure, monitored pilot.
• 90 days:
  Release a production‑ready AI application with documentation and operational runbooks.

• Build AI applications that move from concept to real business value.
• Operate at the intersection of business strategy, engineering, and AI innovation.

PLEASE NOTE WE WILL NOT BE ENTERTAINING THIRD-PARTIES FOR THIS OPPORTUNITY