Role: AI Engineer (Senior)
Year: 2026
Qualification: Not Specified
Experience (years): 5-10
Job description:
• • 6-12 years of software engineering experience, with at least 2 years focused on AI/ML application development.
• • Hands-on experience shipping LLM-powered applications to real users or stakeholders: RAG pipelines, prompt engineering at system level, agentic workflows.
• • Production-level proficiency in Python and/or TypeScript for rapid prototyping.
• • Experience with cloud AI platforms—AWS Bedrock strongly preferred; SageMaker, Azure AI, or Anthropic Claude acceptable.
• • Working experience with agentic AI frameworks: LangChain, LangGraph, CrewAI, AWS Strands Agents, Claude Managed Agents, AWS Agentcore, or equivalent.
• • Strong API integration skills: REST, webhooks, MCP or similar agent-to-service patterns.
• • Demonstrated ability to facilitate business discovery sessions and present demos to technical & non-technical stakeholders.
• • Experience pairing with distributed teams to develop production-grade agentic AI systems.
• • Primary interface with Lead AI Solutions Architects and business stakeholders.
• • Requires strong English communication, executive presence, and async documentation discipline.
• • Bachelor’s degree in computer science, Software Engineering, AI/ML, or related field.
• • Agile/Scrum experience.
• • Builds RAG pipelines, API integrations, agentic workflow components, and prompt systems.
• • Writes transition documentation, contributes to Confluence knowledge base.
• • Must demonstrate strong async communication, self-direction, and clean handoff discipline.
Required Experience
• • Has shipped at least one highly performant and reliable production grade LLM-powered agentic AI application to real users or business stakeholders (not just Kaggle or personal projects).
• • Can write production-quality Python or TypeScript.
• • Can explain what RAG is, what agentic workflows are, and when you would (and would not) use each.
• • Has worked with at least one cloud AI platform (AWS Bedrock preferred).
• • Comfortable with ambiguity — can define scope from an unstructured problem statement.
Preferred
• • Experience with AI evaluation frameworks, prompt testing, and LLM output quality assurance.
• • Background in digital marketing technology, SaaS platforms, or sales/marketing operations.
• • Familiarity with AI Development Lifecycle (AI-DLC) methodologies.
• • Experience with Agent-to-Agent(A2A) integration. 
Technical skills: Python, ML, RAG, VectorDB, APIs, LLMs, AWS/Azure, MCP, Agents, LangChain, LangGraph, Prompt Engineering
Soft skills: Communication, Problem Solving, Analytical Skills