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AI Engineer – GenAI & Agents

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Onsite

AI Engineer – GenAI & Agents

Impelsys

AI Engineer – GenAI & Agents

Skills

SQL QueriesData EngineeringPythonMachine LearningAIAWSGDPR

8 days ago

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Important information


Contract type:

Permanent

Location:

Karnataka, India

Work mode:

Onsite

Published on:

15 October 2026

What they need


Work Location: Bangalore

About Us

We are growing our Data & AI practice, which delivers cloud data platforms, data modernisation and migration, analytics and AI-enabled engineering for global enterprise clients. You will work in cross-functional teams on long-term engagements, using modern cloud technologies and AI-assisted engineering practices. Location: Offshore (India) · Full-time.

Role Summary

Builds LLM applications and AI agents – for clients and for AI-assisted engineering (code conversion, test generation, documentation) – with strong guardrails and measurable results.

Experience

Level

Total experience

Relevant experience (must)

AI Engineer

5–9 years

2+ years building LLM applications / agents; 3+ years Python engineering

Roles & Responsibilities

  • Design and build LLM applications and agents with tool use
  • Build AI-assisted engineering tools: code inventory and conversion, test generation, documentation
  • Engineer prompts and context; build evaluation sets and measure accuracy
  • Implement guardrails: data protection, approved tools, audit trail
  • Track productivity and token cost; optimise with caching and batching
  • Integrate agents with code repositories and CI pipelines

Mandatory Skills

  • Python
  • LLM APIs (Amazon Bedrock, Anthropic, OpenAI or similar)
  • Agent frameworks and tool use
  • Prompt / context engineering and evaluation
  • SQL and code parsing basics

Nice to Have

  • Retrieval-augmented generation
  • Data engineering background
  • AI coding assistants at team scale
  • Cloud security for AI workloads

Also Expected

Clear communication with remote client stakeholders across time zones; Comfortable using AI coding and productivity tools, and reviewing AI-generated work critically; Agile ways of working; ownership and accountability. Certifications: AWS Certified AI Practitioner / ML Engineer (plus).

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