Senior Software Engineer Technology

Position Dossier Senior Software Engineer

About Us

Omega Healthcare Management Services (Omega Healthcare) is an AI-driven healthcare solutions company that partners across the healthcare ecosystem to deliver breakthrough results by reimagining and elevating revenue operations.

With a strong global presence spanning four countries our team of 30000 dedicated professionals collaborate with hospitals physician groups and healthcare providers to streamline operations improve financial performance and elevate patient care outcomes.

We combine our deep domain expertise advanced technology and a customer-centric approach in delivering innovative and scalable healthcare support solutions.

Position Title: Senior Software Engineer

Department: Engineering & Technology Function: AI/ML Platform Engineering

Role Summary

The Senior Software Engineer is a hands-on technical expert responsible for designing developing fine-tuning and evaluating advanced Machine Learning (ML) Deep Learning (DL) Small Language Models (SLMs) and complex Retrieval-Augmented Generation (RAG) architectures. This role focuses on translating enterprise data into measurable business impact by building robust hybrid retrieval pipelines (including GraphRAG) developing agentic scaffolding (harness engineering) and operationalizing state-of-the-art AI research into reliable production systems.

Key Responsibilities

• RAG & GraphRAG Architecture:Design and optimize advanced retrieval pipelines. Move beyond basic vector search by implementing GraphRAG: extracting entities/relationships into knowledge graphs (e.g. Neo4j) applying community detection algorithms and enabling map-reduce summarization for corpus-wide reasoning and complex multi-hop queries.
• Agent Harness Engineering:Build the critical infrastructure (the harness) around language models to ensure reliable agentic behavior. Own the execution runtime including tool routing short/long-term memory management state persistence deterministic guardrails and feedforward/feedback loops for autonomous error correction.
• Advanced Model Development:Design build and deploy specialized SLM and DL solutions. Apply deep statistical rigor to address class-imbalance long-tail coverage and model calibration.
• NLP & Language Modeling:Build solutions utilizing Transformers embeddings and language-model fine-tuning. Adapt base SLMs to domain-specific use cases using multi-adapter strategies (LoRA / QLoRA / PEFT).
• Evaluation & Retrieval Quality:Drive eval-driven iteration for both agents and retrieval systems. Establish benchmarks for generative outputs context relevance and GraphRAG path accuracy. Maintain human-curated golden evaluation datasets under double-blind multi-annotator adjudication.
• Data Engineering & Vector/Graph Storage:Own large-scale extraction pipelines. Manage both Vector Databases for semantic search and Graph Databases for explicit relationship mapping ensuring strict train/eval separation.
• Technical Execution:Write expert-level highly optimized Python code Graph query languages (Cypher/Gremlin) and complex SQL queries to interact with large production data stores.

Required Skills & Expertise

• RAG GraphRAG & Vector Search:Hands-on experience with Microsoft GraphRAG or custom GraphRAG implementations. Proficiency in Knowledge Graphs (Neo4j Amazon Neptune) Graph query languages (Cypher Gremlin) Vector Databases (Pinecone Milvus) and Hybrid Search.
• Agent Harnessing & Orchestration:Frameworks for multi-agent workflows (LangGraph LlamaIndex) memory architecture tool integration (MCP) and safety guardrails (Guardrails AI NeMo Guardrails).
• Classical ML & Deep Learning:Random Forest SVM Boosting/Bagging CNN RNN LSTM Transformer architectures.
• NLP & LLM/SLM Fine-Tuning:Hands-on experience with LoRA QLoRA PEFT quantization and model distillation.
• Frameworks & Tooling:PyTorch Hugging Face (Transformers/TRL/PEFT) unsloth/bitsandbytes.
• Programming:Expert-level Python programming advanced SQL and data pipeline optimization.
• Evaluation & Metrics:RAGAS TruLens LLM-as-a-judge frameworks and robust quantitative metric tracking.

Preferred / Nice to Have

• Domain Knowledge:Strong preference for experience within the Healthcare and Medical domain specifically including Medical Coding knowledge.
• Experience with RHLF/GRPO-style reward modeling.
• Contributions to open-source ML RAG or Agent tooling / published research.
• Constrained-hardware or edge-GPU model optimization.
• Computer Vision exposure.

Educational Qualification

• BE / BTech / ME / MTech / MCA in Computer Science Statistics Mathematics or a related field.
• PhD preferred for candidates with a strong research focus.

Experience

• 58 years of applied experience in Data Science Machine Learning and Deep Learning.
• 2 years of hands-on experience building fine-tuning and evaluating production RAG GraphRAG and LLM/agentic workflows.
• Proven track record of developing and deploying advanced NLP models to production environments.

Work Schedule

Day Shift

Required Experience:

Senior IC