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Mid-level ML/LLM role in a metro with broad skill demands increases candidate competition.
Requires agentic LLM production experience and enterprise decisioning expertise, reducing cross-industry transferability.
Explicit years, mandatory ML/LLM production experience and specific tech stack create strict hiring filters.
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Lead technical architecture and design for agentic AI features on the Aera Decision Platform, including multi-step autonomous agent workflows with human checkpoints.
Own end-to-end ML system deployment and evaluation, implementing comprehensive evaluation frameworks, offline/online metrics, and production monitoring to ensure reliability and performance.
Optimize AI agent performance and cost through context engineering, prompt caching, model routing, and build observability tools for profiling and troubleshooting agent behavior.
Bachelor’s degree (B.E./B.Tech) in Computer Science, Computer Engineering, or related field.
3–5 years software engineering and architecture experience; at least 2 years designing and deploying ML or LLM-based systems with 6–12 months specific LLM hands-on work.
Strong practical software skills with Python, FastAPI or equivalent, distributed systems (e.g., Ray, Spark), ML frameworks (PyTorch, Hugging Face), containerized microservices (Docker, Kubernetes) and CI/CD tools.
Role based in Pune office (location requirement).
Experienced systems architect who has shipped and owned autonomous AI agents in production with accountability for reliability and evaluation under real-world conditions.
Deep understanding of current agent-based ML engineering practices including context engineering, prompt design, subagent orchestration, and robust eval methodologies.
Strategic thinker with ability to abstract complex business domains into scalable AI building blocks and design enterprise-grade AI infrastructure integrating security, scalability, and observability.