How to Apply:

Please submit your application to [email protected]

Job Title: Associate AI Engineer

Location: Bangalore, India

Department: IT

Position Summary:

As PennEngineering accelerates its Speed of Now transformation (respond in 1 hour, quote in 1 day, samples in 1 week, finished product in 1 month), we are building an internal capability to design, develop, and deploy AI-powered workflows, automation, and agentic solutions that improve speed, consistency, and quality across the business.

As an Associate AI Engineer, you will contribute to this mission by building and testing AI-powered components and lightweight agentic solutions under the close guidance of experienced engineers. You will be exposed to the full lifecycle of production AI — from understanding assigned requirements to implementing, testing, and supporting agents that run in live enterprise environments. This role operates as part of a cross-functional delivery model, supported by solution architecture, IS/IT engineering, DevOps, and engagement with business stakeholders and subject-matter experts.

Key Responsibility

1. AI Development & Delivery
   • Implement assigned AI-powered workflow components, chatbot flows, and lightweight agentic tasks using
   • Python and modern LLM frameworks, under guidance
   • Translate clearly defined requirements and design specifications into working code
   • Apply prompt engineering patterns, basic RAG pipelines, and tool-use configurations as directed by senior
     engineers
   • Write clean, modular, and well-tested code following team standards and code review feedback
   • Contribute to shared libraries of reusable agent components, prompts, and integration connectors
   • Use AI-assisted coding tools (such as Cursor, Claude Code, or Amazon Kiro) as part of your daily development
     workflow to accelerate implementation and learn best practices
2. Agile Delivery
   Participate in the team’s iterative agile delivery model:
   • Attend and contribute to sprint planning, stand-ups, retrospectives, and demo sessions
   • Pick up clearly scoped tasks from the sprint backlog and deliver them to definition of done
   • Raise blockers and dependencies early and communicate progress clearly
   • Support testing and validation activities alongside business SMEs
   • Document implementation details, agent configurations, and integration notes for knowledge sharing
3. Integration & Tooling
   • Implement API integrations to connect AI components with enterprise platforms (ERP, CRM, document systems) following established patterns
   • Work with AWS services including Lambda, S3, API Gateway, and Bedrock under guidance of senior engineers
   • Follow CI/CD practices to deploy AI solutions into staging and production environments
   • Add basic telemetry, logging, and monitoring to agent components as directed

Requirements:

• Bachelor’s degree in Computer Science, Software Engineering, Data Science, or a related technical field (2024 or 2025 graduate)
• Solid foundation in Python — you can write clean functions, work with APIs, and debug independently
• Foundational understanding of Large Language Models, prompt engineering, and how LLM APIs work (OpenAI,
  Anthropic, AWS Bedrock, or similar)
• Exposure to at least one AI/ML or agent framework such as LangChain, LangGraph, LlamaIndex, or CrewAI
  through coursework, personal projects, or internships
• Familiarity with REST APIs, JSON, and basic data structures
• Working knowledge of Git and version control practices
• Hands-on familiarity with at least one AI-assisted coding tool (Cursor, Claude Code, Amazon Kiro, GitHub Copilot,
  or similar) — you use these tools actively to write, review, and improve code
• Strong communication skills — written and verbal

Preferred Qualifications:

• Internship or project experience building AI-powered applications or chatbots
• Hands-on experience with any cloud platform (AWS, Azure, or GCP) — even at student or free-tier level
• Exposure to vector databases such as FAISS, Pinecone, Weaviate, or pgvector
• Personal projects or GitHub repositories that demonstrate initiative and curiosity
• Familiarity with containerisation basics (Docker) and REST API development
• Interest in enterprise domains — manufacturing, supply chain, operations, or customer experience
• Familiarity with agile methodologies and sprint-based delivery practices