Job description

About the Role: 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. The AI Engineer is responsible for converting validated business user stories into production-ready AI-powered workflows and AI agents. Some use cases will be addressed through AI-driven workflow automation, while others will require multi-step agentic AI. This role operates as part of a cross-functional delivery model, supported by solution architecture, IS/IT engineering, DevOps, as well as engagement with business stakeholders and subject-matter experts .

- 3-6yearsofoverall software engineering experience, with at least 2 years focused on AI/LLM application development and agentic systems
- Production experience building and operating multi-step AI agents using LangChain, LangGraph, CrewAI, AutoGen, AWS Bedrock Agents, or equivalent
- StrongPythonengineering skills well-structured, testable, production-quality code
- Hands-onexperience with RAG architectures: chunking strategies, embedding models, vector store selection, retrieval optimization, and re-ranking
- Practical knowledge of prompt engineering at scale: structured prompts, chain-of-thought, few-shot design, and prompt evaluation
- Experience with AWScloud services in a production context (Lambda, Bedrock, ECS, S3, API Gateway, CloudWatch)




- WorkingknowledgeofCI/CD practices and deploying AI solutions through automated pipelines
- Understanding of AI observability: logging agent reasoning traces, tracking token usage, monitoring for quality drift
- Proficient in the use of AI-assisted coding tools (Cursor, Claude Code, Amazon Kiro, or similar) as a core part of your engineering workflow with the ability to define, follow, and improve structured coding workflows that leverage these tools effectively
- Strongcommunication skills able to translate technical designs into transparent explanations for non-technical stakeholders
- Bachelors degree in computer science, Engineering, or a related technical field Preferred Qualifications
- Experience with AWSQuick Suite or similar enterprise AI platforms
- Experience with structured agent evaluation frameworks and LLM testing methodologies (e.g., LangSmith, RAGAS, or custom harnesses)
- Familiarity with Model Context Protocol (MCP) and emerging standards for tool-use and agent interoperability
- Experience with fine-tuning or adapting open-source models (Llama, Mistral, or similar) for domain-specific tasks
- Knowledgeofdataengineering, ETL pipelines, and working with enterprise data platforms (Snowflake, Databricks, or similar)
- Experience in manufacturing, supply chain, or industrial environments • Familiarity with agile methodologies and product development practices
- Experience with multimodal AI applications — document understanding, image analysis, or structured data extraction

📌 Direct Walk-in @ Bangalore / Senior Artificial Intelligence Engineer (Karnataka)
🏢 MKS Vision
📍 Karnataka