Job description
GEN AI TX.
We are looking for US Native
Client: HP
Day1: Onsite
No of positions: 2
What you will do:
Build agentic features, hands-on. Work alongside senior engineers to design and ship AI-powered remediation capabilities: agent workflows, retrieval pipelines, evaluation loops.
Write production code daily. Java/Spring Boot microservices and AI integrations on AWS.
Learn the full lifecycle. From an idea in a design doc to something running in production, instrumented, monitored, and improved based on real usage.
Bring fresh eyes. You're closer to the newest models, frameworks, and techniques than engineers who've been heads-down in one stack for a decade we want that perspective in the room, not just deference to seniority.
Grow fast. Work directly with senior engineers who'll push your technical depth, and take on more ownership as you earn it.
Our stack
Java / Spring Boot microservices on AWS (Lambda, SQS, SNS, IAM, CloudWatch). AI stack: AWS Bedrock and AgentCore, MCP for tool integration, RAG pipelines with vector and graph-based retrieval, LLM-as-judge evaluation. Some Python and Go at the edges. You won't know all of this we're more interested in how fast you pick things up than what's already on your resume.
What you will bring:
4+ years building software professionally you've shipped real features, not just coursework or side projects, and you understand what "production" demands.
Genuine curiosity about AI/agentic systems you've built something with LLMs or agents, even outside of work: a side project, a hackathon entry, an experiment that didn't ship. We want to hear about it.
Solid engineering fundamentals distributed systems basics, APIs, cloud infrastructure (AWS). You need to know what good code and good design look like.
You experiment and iterate ideas quickly and bring new perspectives
Nice to have
Experience with multiple LLM APIs or agent frameworks Python or Go POCs using AI for coding, automation, or data work Contributions to open source AI/ML tooling.
We are looking for US Native
Client: HP
Day1: Onsite
No of positions: 2
What you will do:
Build agentic features, hands-on. Work alongside senior engineers to design and ship AI-powered remediation capabilities: agent workflows, retrieval pipelines, evaluation loops.
Write production code daily. Java/Spring Boot microservices and AI integrations on AWS.
Learn the full lifecycle. From an idea in a design doc to something running in production, instrumented, monitored, and improved based on real usage.
Bring fresh eyes. You're closer to the newest models, frameworks, and techniques than engineers who've been heads-down in one stack for a decade we want that perspective in the room, not just deference to seniority.
Grow fast. Work directly with senior engineers who'll push your technical depth, and take on more ownership as you earn it.
Our stack
Java / Spring Boot microservices on AWS (Lambda, SQS, SNS, IAM, CloudWatch). AI stack: AWS Bedrock and AgentCore, MCP for tool integration, RAG pipelines with vector and graph-based retrieval, LLM-as-judge evaluation. Some Python and Go at the edges. You won't know all of this we're more interested in how fast you pick things up than what's already on your resume.
What you will bring:
4+ years building software professionally you've shipped real features, not just coursework or side projects, and you understand what "production" demands.
Genuine curiosity about AI/agentic systems you've built something with LLMs or agents, even outside of work: a side project, a hackathon entry, an experiment that didn't ship. We want to hear about it.
Solid engineering fundamentals distributed systems basics, APIs, cloud infrastructure (AWS). You need to know what good code and good design look like.
You experiment and iterate ideas quickly and bring new perspectives
Nice to have
Experience with multiple LLM APIs or agent frameworks Python or Go POCs using AI for coding, automation, or data work Contributions to open source AI/ML tooling.
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