Software Engineer ( Python + PySpark + Agentic AI ) - 5 + Years

Infor Inc.; Hyderabad; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Infor Inc. in Hyderabad is seeking a Software Engineer with 5+ years of experience in Python and PySpark to design, develop, and optimize large-scale data pipelines. You will build agentic AI features and RAG workflows on AWS, applying strong Python and Spark skills to data processing on EMR on EKS.

You will design tools for agents, implement retrieval-augmented pipelines, and ensure guardrails with human-in-the-loop review. Collaboration with engineers and data scientists is essential.

Qualifications

• Solid production Python 3 code experience with web frameworks (FastAPI/Flask/Django).
• Hands-on PySpark experience and SQL for large-scale data processing.
• Experience building LLM/agent-based features and tool calling.
• Familiar with big data tech, AWS services, and data governance.

Responsibilities

• Write and tune PySpark jobs on EMR on EKS and Delta Lake at scale.
• Design and build LLM-powered agents and RAG pipelines with guardrails.
• Connect agents to internal systems via APIs and data sources.
• Develop Python services, Kafka data movement, and observability hooks.

Skills

Python

PySpark

SQL

AWS

Docker

Kubernetes

LLM / Agentic AI

EMR on EKS

Delta Lake

Kafka

Git

pytest

Tools

EMR on EKS

Delta Lake

Kafka

Docker

Kubernetes

Git

Job description

Software Engineer ( Python + PySpark + Agentic AI ) - 5 + Years

Department: Development

Employment Type: Full Time

Location: Hyderabad

Description

We are looking for an experienced Python + PySpark Developer with a strong background in designing, developing, and optimizing large-scale data processing solutions. The ideal candidate should have strong expertise in Python, PySpark, SQL, and big data technologies. You will build the large-scale data pipelines and agentic AI features that power our platform on AWS. You will apply strong Python and PySpark skills to data processing on EMR on EKS, and build LLM-based agents that assist and automate work on our data under human oversight.

A Typical Day in the Life Includes:

• Write and tune PySpark jobs on EMR (EMR on EKS) and Delta Lake to prepare and transform data at scale
• Design and build LLM-powered agents that plan tasks, call tools, and propose or apply actions against our services and data, under confidence thresholds and human-in-the-loop review
• Define the tools and APIs agents can use, and connect agents to internal systems (e.g., via Model Context Protocol)
• Build retrieval-augmented (RAG) pipelines: chunking, embeddings, vector search, and grounding responses in our data
• Design agent workflows with clear guardrails, confidence gating, human-in-the-loop exception handling, and fallback behavior
• Write prompts and evaluation harnesses; run evaluation in CI and measure agent quality, cost, and latency, then iterate
• Build and maintain Python services and shared libraries, and Kafka producers/consumers for moving data between services
• Serve agents behind APIs and monitor them with LLM/agent observability (quality, cost, latency, failures)
• Write design docs and collaborate with engineers and data scientists on architecture decisions
• Use AI coding agents in your own day-to-day workflow while owning correctness and quality

Basic Qualifications:

• These are the core skills we screen for. A strong candidate has all three.
• Python 3 — solid experience writing production code, with strong fundamentals and readable, tested code, using a web framework such as FastAPI, Flask, or Django
• PySpark & SQL — hands-on experience writing and tuning Spark jobs on EMR (we run EMR on EKS), reading/writing Delta Lake tables, and strong SQL for large-scale data
• Agentic AI — hands-on experience building LLM or agent-based features: tool/function calling, multi-step agent workflows, RAG, and grounding output in real data.
• Experience writing production Python 3, including designing and optimizing large-scale data processing solutions
• Experience building services or APIs with a Python web framework such as FastAPI, Flask, or Django
• Hands-on experience with Spark / PySpark, ideally on EMR (EMR on EKS a plus)
• Strong SQL and familiarity with big data technologies
• Hands-on experience building LLM or agent-based features (tool calling, function calling, or multi-step agent workflows)
• Experience with an agent or LLM framework or platform such as Amazon Bedrock, LangChain, LangGraph, LlamaIndex, or the OpenAI/Anthropic SDKs
• Experience with RAG: embeddings, vector search, and grounding model output in real data
• Practical prompt engineering and experience evaluating LLM/agent output for quality and reliability
• Experience handling sensitive data and PII responsibly, including data-governance and privacy considerations when sending data to external LLMs
• Experience with at least one database (MongoDB/DocumentDB, PostgreSQL, or similar)
• Experience with AWS services such as S3 and EMR
• Experience writing tests with pytest (or similar) and working with Git
• Comfortable with Docker and Linux
• Practical experience using AI coding assistants or agents (e.g., Kiro, Cursor, GitHub Copilot, Claude Code) in real projects
• Strong communication: able to write design docs and collaborate across teams

Preferred Qualifications:

• Experience with Model Context Protocol (MCP) or wiring agents to external tools and data sources
• Experience keeping LLM systems reliable: guardrails, evaluation pipelines, cost/latency tuning, caching
• LLM/agent observability and lifecycle experience: prompt/version management, monitoring, and quality regression detection
• Solid ML fundamentals and quality metrics (precision, recall, F1); familiarity with scikit-learn, pandas, NumPy
• Delta Lake, AWS Glue, and Athena
• Kafka streaming pipelines
• Kubernetes / EKS, Helm, and GitOps deployment
• Experience in a polyglot microservice environment (Node.js / Python / Java)
• Awareness of bias and explainability in AI systems