Senior AI/ Machine Learning Engineer

1 month ago

Pune, IndiaSenior

Responsibilities

Set technical direction for agentic systems, including architecture, design documentation, build-versus-buy decisions, model selection, and framework adoption.
Own the agentic platform end to end, including multi-step reasoning, tool use, subagent orchestration, agent memory, long-horizon loops, and human checkpoints.
Establish organization-wide offline and online evaluation practices, golden datasets, LLM-as-judge pipelines, regression gates, and non-deterministic test suites.
Build reusable platform infrastructure including shared tools and skills, MCP servers, context strategies, prompt caching, and routing layers.
Drive performance, cost, and reliability through context engineering, compression, parallel and asynchronous tool calls, model routing, structured outputs, token budgets, and inference optimization.
Mentor engineers, review designs and agent-generated code, and define production-readiness standards for non-deterministic systems.
Design agent security controls including tool permissioning, sandboxing, prompt-injection resistance, and blast-radius management.
Partner with Data Science, Engineering, DevOps, and Product to solve ambiguous business problems and evaluate emerging AI techniques.

B.E. or B.Tech in Computer Science, Computer Engineering, or a related field.
5–8 years of software engineering and architecture experience, including at least 3 years designing and deploying ML or LLM-based systems.
At least 12 months of experience building agentic or LLM-powered systems that reached production.
Experience setting technical direction, owning architectural decisions, and taking systems from architecture through production reliability.
Deep Python experience and FastAPI or an equivalent framework for production services.
Strong distributed-systems fundamentals and experience with large datasets and ML pipelines such as Ray or Spark.
Hands-on experience with PyTorch, Hugging Face, scikit-learn, and pandas.
Experience with containerized microservices using Docker and Kubernetes, plus Git, Jenkins, and Jira.
Fluency in agentic engineering practices including context engineering, tool and skill design, subagent patterns, agent memory, evaluations, LLM-as-judge, structured outputs, prompt caching, and RAG.
Preferred: technical workstream leadership or mentoring experience, GoLang, vector databases, Temporal, Kafka, Pulsar, Redis, agent observability and experiment-tracking tools, fine-tuning, multimodal AI, serverless AI infrastructure, and enterprise constraints such as multi-tenancy, data isolation, compliance, or regulated deployments.

Competitive salary and company stock options.
Medical, group medical, term insurance, accidental insurance, paid time off, and maternity leave.
Unlimited access to online professional courses and people-manager development programs.
Flexible working environment supporting work-life balance.
Fully stocked office kitchen with snacks and beverages.
The role is based in the Pune office.

201-500 employees