Software Engineer - AI/ML

Role & responsibilities

Software Engineer (AI/ML)

modern AI stacks

• Design, build, and deploy

  AI-powered tools, assistants, and automation systems

  to support internal operations.
• Develop, optimize, and integrate

  Python-based APIs and microservices

  for AI workflows.
• Implement

  Retrieval-Augmented Generation (RAG)

  pipelines, custom

  LangChain

  agents, and

  LLM-based solutions

  for business use cases.
• Work with structured/unstructured data; manage

  database integrations (SQL/NoSQL)

  and knowledge retrieval systems.
• Evaluate and integrate

  open-source and commercial AI models

  , fine-tuning or prompting as needed.
• Collaborate with cross-functional teams to identify automation opportunities and prototype solutions quickly.
• Implement

  observability and monitoring

  for AI services in production (AI-Ops best practices).
• Stay updated on emerging trends in

  Generative AI, agent frameworks, and MLOps

  tools.

Required Skills & Experience

• 14 years

  of professional experience in software engineering or applied AI/ML.
• Strong proficiency in

  Python

  , including use of libraries for APIs, data handling, and AI model integration.
• Practical experience with

  AI frameworks/tools

  such as

  LangChain, LlamaIndex, or similar orchestration libraries

  .
• Good understanding of

  LLMs (e.g., GPT, Claude, Gemini, Mistral)

  ,

  RAG

  , and

  prompt engineering

  techniques.
• Experience working with

  APIs

  ,

  databases

  (SQL/NoSQL), and

  data pipelines

  .
• Hands-on experience with

  generative AI or agent-based systems

  in real-world or production contexts (not only course projects).
• Familiarity with

  Git, CI/CD, Docker, or cloud platforms (AWS/GCP/Azure)

  is a plus.

Preferred candidate profile

• Experience in

  AI-Ops, automation tools, or internal AI enablement projects

  .
• Prior experience building

  chatbots, assistants, or autonomous agents

  .
• Exposure to

  vector databases (Pinecone, Chroma, Weaviate, etc.)

  .
• Working knowledge of

  data orchestration, prompt pipelines, or model evaluation frameworks

  .