Job Summary

ML & AI Engineer
. Must haves
 1. Python literacy - min 2years+ working on production grade LLM based applications
2. Software Engineering - strong understanding of microservices architecture, CI/CD pipelines, event driven architecture
3. AI Engineering - RAG pipelines, prompt engineering, VertexAI experience, LLMOps and runtime evaluation/monitoring
4. Data engineering - scaled data pipelines using python/spark. GCP native services: BQ, Spanner, Dataflow, Firestore
. Nice to haves
 1. AgenticAI - Langgraph, ADK, CrewAI, multi-agent architectures - experience in building deployable solutions, not jupyter notebooks
2. Data ontologies - graphical approaches to data storage + retrieval

Key Responsibilities

1. To be responsible for providing technical guidance to a team of developers, enhancing their technical capabilities and increasing productivity.
2. To conduct comprehensive code reviews, establish and oversee quality assurance processes, performance optimization , implementation of best practices and coding standards to ensure successful delivery of complex projects.
3. To ensure process compliance in the assigned module| and participate in technical discussions/review as a technical consultant for feasibility study (technical alternatives, best packages, supporting architecture best practices, technical risks, breakdown into components, estimations).
4. To collaborate with stakeholders to define project scope, objectives, deliverables and accordingly prepare and submit status reports for minimizing exposure & closure of escalations.

Skill Requirements

null

Other Requirements

null