Infinite Computer Solutions
Job Description
Build, fine‑tune, and evaluate ML/LLM models for classification, prediction, summarization, RAG, and agentic workflows.
Conduct experimentation, A/B testing, and performance tuning.
Implement agentic frameworks (multi‑step reasoning, workflows, tool use).
Integrate AI agents into orchestration layers (Drools, microservices, API gateways).
Build domain‑specific ontologies, embeddings, vector search, and retrieval layers.
Build ETL/ELT pipelines, feature stores, and real‑time data ingestion using Python and SQL.
Work with structured/unstructured data including EDI, FHIR, PDFs, medical records.
Develop secure, scalable APIs (REST/GraphQL) for embedding AI into product workflows.
Integrate AI modules with microservices, Postgres DB, event queues, and messaging layers.
Work closely with DevOps to deploy models into containerized environments (AWS, Docker, Lambda).
Implement monitoring, guardrails, safety filters, hallucination‑mitigation and auditability.
Ensure HIPAA, PHI, SOC2, CMS‑compliant AI operations.
Drive MLOps best practices including CI/CD pipelines, versioning, and model governance.
Work with product, clinical, engineering, and client teams to translate real‑world use cases into scalable AI solutions.
Collaborate with SMEs in UM/CM, provider operations, risk, fraud, and claims workflows.
Technical Skills
Strong Python development (FastAPI, LangChain, LlamaIndex, PyTorch, transformers).
Hands‑on LLM experience (OpenAI, AWS Bedrock, local models like Llama, Mistral).
Experience with vector databases (Pinecone, PGVector, Chroma).
Solid SQL experience (PostgreSQL preferred).
Experience building microservices and event‑driven systems.
Knowledge of AWS stack: Lambda, S3, EC2, API Gateway, Step Functions.
Experience with AI agents, RAG pipelines, and orchestration frameworks.
Familiarity with healthcare standards (FHIR, EDI 278/837/835) is a strong plus.
Soft Skills
Strong problem‑solving, analytical thinking, and debugging skills.
Ability to work in fast‑paced, ambiguous, product‑driven environments.
Excellent communication skills for cross‑functional collaboration.
Preferred Qualifications
12–18+ years of experience in AI/ML engineering or software engineering with AI integration.
Experience in payers, providers, health tech, or regulated industries.
Exposure to rule engines (Drools/Blaze/Sparkling Logic) and BPM/orchestration systems.
Experience with RPA, document processing, OCR/NLP, or medical record extraction.
Metadata
Seniority level: Mid‑Senior level
Employment type: Full‑time
Job function: Project Management and Information Technology
Industries: IT Services and IT Consulting
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Build, fine‑tune, and evaluate ML/LLM models for classification, prediction, summarization, RAG, and agentic workflows.
Conduct experimentation, A/B testing, and performance tuning.
Implement agentic frameworks (multi‑step reasoning, workflows, tool use).
Integrate AI agents into orchestration layers (Drools, microservices, API gateways).
Build domain‑specific ontologies, embeddings, vector search, and retrieval layers.
Build ETL/ELT pipelines, feature stores, and real‑time data ingestion using Python and SQL.
Work with structured/unstructured data including EDI, FHIR, PDFs, medical records.
Develop secure, scalable APIs (REST/GraphQL) for embedding AI into product workflows.
Integrate AI modules with microservices, Postgres DB, event queues, and messaging layers.
Work closely with DevOps to deploy models into containerized environments (AWS, Docker, Lambda).
Implement monitoring, guardrails, safety filters, hallucination‑mitigation and auditability.
Ensure HIPAA, PHI, SOC2, CMS‑compliant AI operations.
Drive MLOps best practices including CI/CD pipelines, versioning, and model governance.
Work with product, clinical, engineering, and client teams to translate real‑world use cases into scalable AI solutions.
Collaborate with SMEs in UM/CM, provider operations, risk, fraud, and claims workflows.
Technical Skills
Strong Python development (FastAPI, LangChain, LlamaIndex, PyTorch, transformers).
Hands‑on LLM experience (OpenAI, AWS Bedrock, local models like Llama, Mistral).
Experience with vector databases (Pinecone, PGVector, Chroma).
Solid SQL experience (PostgreSQL preferred).
Experience building microservices and event‑driven systems.
Knowledge of AWS stack: Lambda, S3, EC2, API Gateway, Step Functions.
Experience with AI agents, RAG pipelines, and orchestration frameworks.
Familiarity with healthcare standards (FHIR, EDI 278/837/835) is a strong plus.
Soft Skills
Strong problem‑solving, analytical thinking, and debugging skills.
Ability to work in fast‑paced, ambiguous, product‑driven environments.
Excellent communication skills for cross‑functional collaboration.
Preferred Qualifications
12–18+ years of experience in AI/ML engineering or software engineering with AI integration.
Experience in payers, providers, health tech, or regulated industries.
Exposure to rule engines (Drools/Blaze/Sparkling Logic) and BPM/orchestration systems.
Experience with RPA, document processing, OCR/NLP, or medical record extraction.
Metadata
Seniority level: Mid‑Senior level
Employment type: Full‑time
Job function: Project Management and Information Technology
Industries: IT Services and IT Consulting
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