Senior AI Engineer (Generative AI & Agentic Systems)

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Machine Learning EngineerData

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Quick Summary

Key Responsibilities

In this role, you will design, build, and deploy production-grade Generative AI and Agentic AI solutions that automate complex business processes and augment enterprise workflows.

Technical Tools

Machine Learning EngineerData

Responsibilities

~1 min read

→Design and develop LLM-powered applications, including RAG (Retrieval-Augmented Generation) pipelines, agentic workflows, and multi-step autonomous agents using frameworks such as LangChain and LangGraph
→Build and optimize retrieval architectures using vector databases (e.g., ChromaDB) and semantic search to ground LLM responses in enterprise data.
→Apply prompt engineering techniques to improve accuracy, reliability, and cost-efficiency of LLM-based solutions across both hosted (OpenAI API, Claude Code, Claude) and offline/self-hosted models.
→Serve as a technical point of contact for clients and internal stakeholders on AI solution design, feasibility, and delivery timelines.
→Integrate GenAI solutions with existing enterprise systems via REST APIs, webhooks, and cloud services (AWS Lambda, Azure) to ensure secure, scalable deployment.
→Extend or modernize existing RPA/automation assets (e.g., Blue Prism, code-based automation frameworks) by incorporating AI-driven decisioning and self-healing capabilities.
→Coordinate the development, review, and documentation of AI solution deliverables (solution design documents, evaluation reports, deployment runbooks).
→Establish CI/CD and monitoring practices for AI applications using tools such as Git, GitHub Actions, Jenkins, and Splunk.
→Identify risks related to model performance, data quality, and security; mitigate roadblocks during development, testing, or deployment.

Requirements

~1 min read

Bachelor's degree in Computer Science, Information Technology, Engineering, or equivalent education and experience.
Minimum 5–8 years of software development experience, including at least 2 years building Generative AI or Agentic AI applications in production.
Hands-on experience with LLM application frameworks (LangChain, LangGraph) and LLM APIs (OpenAI API or equivalent).
Strong understanding of RAG architectures, prompt engineering, and vector databases (e.g., ChromaDB or similar).
Proficiency in Python; working knowledge of C#, JavaScript, and SQL.
Experience with cloud platforms and services (AWS Lambda, Amazon DynamoDB, Azure) and REST API integration.
Experience with DevOps tooling (Git/GitHub, GitHub Actions, Jenkins) and application monitoring (e.g., Splunk).
Background in RPA or process automation (e.g., Blue Prism, UiPath, or Automation Anywhere) is a strong plus.
Understanding of IT delivery methodologies (Agile, Lean, ITIL).
Excellent planning, problem-solving, and technical leadership skills.

Self-motivated and able to take initiative with minimal supervision.
Senior AI Developer (Generative AI & Agentic Systems)
Effective communicator, able to translate technical AI concepts for non-technical stakeholders.
Highly organized and methodical, while comfortable adapting to changing requirements.
Strong analytical and problem-solving skills, with a bias toward experimentation and iteration.
High emotional intelligence and cross-functional collaboration skills.
Demonstrated willingness to dive into implementation details to guide projects to completion.
Team-oriented, with an interest in mentoring and knowledge-sharing.
Curious and committed to staying current with the fast-evolving GenAI/Agentic AI landscape.