Key Responsibilities
Own the design and delivery of production AI systems end-to-end, from problem framing and solution architecture to deployment, monitoring, and iteration.
Lead context engineering for our AI workflows: design how information, instructions, retrieval, and tools are composed so LLM-based systems behave reliably at scale.
Make technical decisions independently, evaluate tradeoffs, choose architectures, and commit to a direction without requiring escalation for every ambiguity.
Mentor and unblock junior AI engineers; raise the team's bar on systems thinking, prompt/context design, and software engineering rigor.
Translate ambiguous business problems into well-scoped, scalable AI solutions, not one-off demos or POCs.
Operationalize LLMs and AI agents, including prompt orchestration, chaining, evaluation, and observability.
Build evaluation frameworks to measure and improve reliability, quality, and auditability of AI outputs.
Apply solid software engineering principles to AI work: code review, testing, CI/CD, monitoring, rollback mechanisms,



and maintainable design.
Collaborate async with US-based engineers, data scientists, and product managers; proactively communicate decisions, blockers, and progress across time zones.
Hire and grow the India AI team as we scale, setting the standard for what outstanding AI engineering looks like.
Debug complex issues and perform root cause analysis across model pipelines, infrastructure, and product layers.

Qualifications
BS or MS in Computer Science, Statistics, or Mathematics, or equivalent experience.
6+ years of software engineering experience, including 3+ years building and shipping production AI/ML systems.
2+ years of experience leading or managing engineers, you've mentored people, owned delivery for a team, and know how to unblock others because you've repeatedly unblocked yourself.
Proven track record of building and owning real production systems, not just experiments, noteboo

📌 Engineering Lead Bengaluru (India)
🏢 Genios AI
📍 India