Specialist - Software Engineering

Company Overview

Acentra Health exists to empower better health outcomes through technology, services, and clinical expertise. Our mission is to innovate health solutions that deliver maximum value and impact.

Lead the Way is our rallying cry at Acentra Health. Think of it as an open invitation to embrace the mission of the company; to actively engage in problem-solving; and to take ownership of your work every day. Acentra Health offers you unparalleled opportunities. In fact, you have all you need to take charge of your career and accelerate better outcomes – making this a great time to join our team of passionate individuals dedicated to being a vital partner for health solutions in the public sector.

At Acentra Health, we embrace emerging technologies, including artificial intelligence and advanced analytics that can be utilized to improve processes, enhance decision-making, and drive better health outcomes. We value professionals who are curious about new technologies and motivated to use innovative tools to increase efficiency, quality, and impact in their roles.

Job Summary and Responsibilities

Acentra Health’s AI Studio is the hub for AI innovation and enablement for the Global Delivery Organization. Our mandate is to prove value with production-grade pilots/MVPs and then transfer successful solutions to business lines for scale. We work through a L0–L5 stage-gate, partner with Programs and Operations to build responsibly with privacy-first design, healthcare-grade quality, and measurable business impact.

You’ll build production-grade pilots/MVPs and the reusable components behind them. Expect hands-on work with LLMs, RAG, agentic workflows, and healthcare-grade security/observability. You’ll collaborate with product, portfolio, data, and platform teams to take solutions from discovery to L4 execution and clean hand-off for scale

Design & Build: Implement LLM-powered services (RAG/ agents/ classifiers/ extractors), APIs, and microservices with strong reliability, testing, and observability.

Evaluation & Guardrails: Implement offline/online evals, red-team tests, prompt/response guardrails, bias/privacy checks, and cost/latency tracking.

Data & Integration: Connect to internal data platforms and line-of-business apps; build retrieval pipelines, grounding strategies, and prompt construction.

Standards & Practices: Support and implement MLOps/LLMOps practices such as CI/CD pipelines, versioning, monitoring, retraining, and governance.

Operational Readiness: Produce runbooks, SLOs, dashboards, and IaC/CI-CD; partner with InfoSec/Compliance on PHI handling and auditability.

Reuse at the Core: Contribute libraries/templates (RAG starters, agent patterns, eval harnesses) to speed the next build.

Job Requirements and Qualifications

Required Qualifications/Experience

• Bachelor’s degree in Computer Science, Data Science, or a related field.
• 4–6 years in software or ML engineering with recent focus on LLM applications.
• Strong Python; experience with one or more: Transformers, vector DBs (FAISS/Pinecone/Weaviate), orchestration (LangChain/LlamaIndex), retrieval pipelines.
• Cloud & DevOps: AWS services, containers (Docker/K8s), CI/CD (GitHub Actions), observability.
• Quality mindset: testing, evals, prompt hygiene, data provenance, and privacy by design

Additional Qualifications

• Healthcare/regulated domain experience preferred.
• Knowledge of healthcare data standards (HL7, FHIR) and compliance (HIPAA).
• Expertise in Document AI/OCR, model monitoring, and application performance management (APM)