Software Engineer - Niche 3 (35) - GenAI Engineer

Required Skills

If you are Interested, please fill this form: -

https://docs.google.com/forms/d/e/1FAIpQLSdrr1iAlbWgkrzfIiW4P13TGym9izzBFKZAa6QkgBbIycDi2w/viewform?usp=publish-editor

- Agentic Development/Observability: Hands-on experience with tools such as Lang Smith, Lang fuse, Data Dog. Building multi-agent services. Exposure to monitoring and tracing multi-agent/LLM workflows concepts, tool-call tracing, latency/cost/drift monitoring, Smart LLM routing, cost optimization, and multi-cloud decisioning (AWS/GCP, etc).

- Agentic Governance: Guardrails and safety controls for autonomous agents, human-in-the-loop design, audit logging, and responsible AI/compliance frameworks.

- Data Strategy: Experience contributing to or advising on enterprise data strategy, data architecture roadmaps, and data-driven decision-making frameworks.

- Dev Data Platforms: Data pipeline design and data engineering fundamentals are mandatory. Hands-on experience with modern data platform tooling (e.g., Databricks, Snowflake,



or similar lakehouse/warehouse platforms) is a plus.

- DevOps: Exposure to CI/CD pipeline design (e.g., Jenkins, GitHub Actions, Azure DevOps), infrastructure as code (Terraform or equivalent), and automated testing/release practices.

Core GenAI Engineering Skills

- Robust programming skills in Python (or similar) for building GenAI applications.

- Experience with LLM application frameworks such as LangChain, LangGraph, Semantic Kernel, or AutoGen.

- Experience with RAG architectures, vector databases (e.g., Pinecone, Weaviate, FAISS, pgvector), and embeddings.

- Familiarity with prompt engineering, fine-tuning/instruction-tuning, and evaluation of LLM outputs.

- Experience integrating with major LLM providers/platforms such as OpenAI, Anthropic, Azure OpenAI, or AWS Bedrock.

- Understanding of MLOps/LLMOps practices for model deployment and lifecycle management.

📌 AIML-Contract to Hire-Bangalore (Bengaluru)
🏢 Artech Infosystems
📍 Bengaluru