AI Engineer

Location: Bengaluru

About the Role
As Penn Engineering 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 agentic AI. This role operates as part of a  cross-functional delivery model , supported by solution architecture, IS/IT engineering, Dev Ops, as well as engagement with business stakeholders and subject-matter experts.

Key Responsibilities
1. AI Development
Partner with the business to identify AI use cases and opportunities
Design, build, and deploy AI-powered workflows, automation, and agentic solutions
Convert user-stories into structured functional designs for AI workflows and agents
Develop secure and scalable agents using AWS technologies up to and including AWS Bedrock and AWS Quick Suite
Maintain an internal library of AI-powered workflows and agents with version control, telemetry, and continuous improvement processes

2. Agile Delivery
Operate in an iterative agile model:
User-story intake and prioritization
AI workflow or agent design and build
Testing and validation with business SMEs
Pilot deployment and data-driven refinement
Establish a predictable pipeline and regular release cadence
Ensure traceability from  user story to AI solution to business outcome

3. Engineering & Integration
Work with the IS team to ensure access to clean, governed, structured data where required
Collaborate with IS solution architects to align designs with enterprise standards
Integrate AI solutions with existing enterprise systems and platforms
Ensure all AI-powered workflows and agents meet corporate security, compliance, and audit requirements

Key KPIs
Number of AI powered workflows, automation and agents deployed tied to validated user stories and process improvements
Cycle-time reduction across targeted processes
% of user stories converted into deployable AI solutions each quarter
Adoption rate of AI-powered workflows and agents among internal users
Measured impact on customer experience, throughput, accuracy, or friction removal
Time-to-deploy (elapsed from user-story sign-off to production launch)

What does success look like?
Success in this role is when Penn Engineering sees a steady, predictable pipeline of working AI powered workflows, automation and agents   that meaningfully improve our employee and customer experience. Most importantly, the role is an accelerator of the company’s AI transformation. You are proactive, iterative, customer-obsessed, data-driven, and blend technical excellence with business impact.

The AI Engineer contributes to Penn Engineering’s broader AI capability by delivering reliable, secure, and practical AI solutions grounded in real business needs, working collaboratively across technology and business teams.

Required Qualifications
3+ years of experience in software engineering, with 1+ years focused on AI/ML development
Working knowledge in Python and modern AI/ML frameworks (e.g., Lang Chain, Llama Index, Hugging Face)
Proven experience with cloud platforms, particularly AWS (Bedrock, Sage Maker, Lambda, etc.)
Deep understanding of LLMs, prompt engineering, RAG architectures, and agentic AI patterns

Experience with MLOps practices, CI/CD pipelines, and production deployment
Knowledge of data engineering, APIs, and system integration
Strong communication skills
Bachelor's degree in Computer Science, Engineering, or related field

Preferred Qualifications

Experience with AWS Quick Suite or similar enterprise AI platforms
Experience in manufacturing, supply chain, or industrial environments
Familiarity with agile methodologies and product development practices