Software Engineer - GenAI & Agentic Systems
This role has been designed as Hybrid with an expectation that you will work on average 2 days per week from an HPE office.
Job Title: Software Engineer - GenAI & Agentic Systems
Designs, and develops advanced Generative AI applications with a specific focus on autonomous agents and multi-agent systems for our enterprise-grade network technology and autonomous platform. Leverages large language models (LLMs) to create reasoning engines that interact with external tools, APIs, and structured data. Specializes in building stateful, cyclic AI workflows using LangGraph to solve complex, non-linear problems in enterprise network.
Translates high-level product requirements into robust Python code, bridging the gap between stochastic LLM outputs and deterministic software systems. Implements Retrieval- mented Generation (RAG), optimizes prompt engineering strategies, and deploys scalable agentic architectures that can visualize, plan, and execute multi-step tasks.
What you will do -
Agentic Architecture Design: Design and implement stateful, multi-agent workflows using LangGraph . Define nodes, edges, and conditional logic to create agents capable of loops, self-correction, and human-in-the-loop interactions.
-
GenAI Application Development: Develop end-to-end GenAI applications in Python , utilizing frameworks like LangChain and LlamaIndex to integrate LLMs (e.g., GPT-4, Claude, Llama 3) with enterprise data and APIs.
-
Tool & Function Calling: Engineer robust "tools" and function-calling interfaces that allow agents to interact with internal databases, perform web searches, or execute code to complete tasks.
-
Performance Optimization: Evaluate and improve agent performance. Move beyond basic accuracy metrics to measure "agent trajectory" quality, token usage efficiency, latency, and success rates in multi-step reasoning tasks.
-
Collaboration & Integration: Collaborate with software engineers to expose agents via APIs (e.g., FastAPI) and integrate them into existing product ecosystems. Explain agent ision-making processes (observability) to non-technical stakeholders.
-
Code Quality & Review: Contribute to design review sessions, specifically focusing on the maintainability of complex graph structures and state management. Provide feedback to peers on Python best practices and asynchronous programming.
-
Prompt Engineering & Fine-Tuning: Design sophisticated system prompts and manage prompt versioning. Occasionally fine-tune Small Language Models (SLMs) for specific domain tasks where latency or cost is a constraint.
-
Prototyping to Production: Rapidly prototype new agent concepts in stand-ups and move successful experiments to production-grade code, handling error recovery and guardrails against hallucination.
What you need to bring
Education and Experience Required
-
Bachelors degree in Computer Science, Artificial Intelligence, Data Science, or a related quantitative field. Master s degree preferred.
-
Typically 2-4 years of total software or data engineering experience.
-
Specific Requirement: At least 1 year of hands-on experience working with Generative AI, or building applications with LangChain/LangGraph.
Knowledge and Skills
Core Technical Skills:
-
Advanced Python: Strong proficiency in Python is non-negotiable, particularly with asynchronous programming (asyncio), Pydantic (for data validation), and typing.
-
GenAI Frameworks: Deep practical knowledge of LangGraph (for graph-based flows) and LangChain . Familiarity with DSPy or AutoGen is a plus.
-
LLM Orchestration: Understanding of Context Windows, Tokenization, Temperature, and the mechanics of Chat APIs (OpenAI, Anthropic, HuggingFace).
Agentic Skills:
-
Graph Theory & Logic: Ability to visualize and implement business logic as directed cyclic graphs (nodes, edges, conditional jumps).
-
NoSQL Databases: Experience with Elasticsearch, redis or vector stores such as Pinecone, Milvus, Qdrant, or PGVector.
Foundational Skills:
-
Software Engineering: Proficient with Git, Docker, and CI/CD pipelines. Experience building and consuming RESTful APIs.
-
Math & Stats: Solid understanding of linear algebra (embeddings) and probability as it relates to model sampling and ision-making.
-
Communication: Ability to demystify "AI Magic" and explain the limitations (e.g., hallucinations) and capabilities of agentic systems to product managers and business stakeholders.
Cloud Architectures, Cross Domain Knowledge, Design Thinking, Development Fundamentals, DevOps, Distributed Computing, Microservices Fluency, Full Stack Development, Security-First Mindset, Solutions Design, Testing & Automation, User Experience (UX)
Job:
Engineering
Job Level:
TCP_02
HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT employer. We do not discriminate on the basis of race, gender, or any other protected category, and all isions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to in ate and grow together. Please click here: Equal Employment Opportunity .
No Fees Notice & Recruitment Fraud Disclaimer
It has come to HPE s attention that there has been an increase in recruitment fraud whereby scammer impersonate HPE or HPE-authorized recruiting agencies and offer fake employment opportunities to candi . These scammers often seek to obtain personal information or ey from candi .
Please note that Hewlett Packard Enterprise (HPE), its direct and indirect subsidiaries and affiliated companies, and its authorized recruitment agencies/vendors will never charge any candi a registration fee, hiring fee, or any other fee in connection with its recruitment and hiring process. The credentials of any hiring agency that claims to be working with HPE for recruitment of talent should be verified by candi and candi shall be solely responsible to conduct such verification. Any candi /individual who relies on the erroneous representations made by fraudulent employment agencies does so at their own risk, and HPE disclaims liability for any damages or claims that result from any such communication.
