Position OverviewWe are seeking a Senior AI Developer to join our engineering team. In this senior role you will help shape and execute our AI/ML strategy, guiding our journey from early generative-AI capabilities into a mature, production-grade AI practice. You will integrate generative-AI features into our products and internal platforms, combine retrieval-augmented generation (RAG) with knowledge graphs to ground model outputs in our domain data, and own AI features end-to-end - model selection, prompt engineering, retrieval, fine-tuning where appropriate, deployment, observability, cost governance, and compliance posture. As a senior individual contributor, you will also provide architectural direction and code-level guidance to existing engineering teams who own day-to-day delivery of supporting backend and data-layer work.
Accountabilities and Responsibilities - Helps set technical direction for AI/ML - evaluates models, frameworks, vector stores, graph databases, evaluation tooling, and orchestration patterns; makes recommendations and leads adoption.
- Designs and implements production generative-AI features using managed foundation-model services, applying guardrails, contextual grounding, structured output, tool use, and agentic workflow patterns.
- Builds retrieval-augmented generation (RAG) pipelines - document ingestion, chunking, embeddings, vector search, hybrid retrieval, and reranking - selecting the storage approach that best fits each use case.
- Designs and operates knowledge graphs to model the domain - schema and ontology design, entity resolution, relationship extraction, and integration with LLM workflows (GraphRAG, hybrid graph + vector retrieval).
- Trains and fine-tunes models where it produces measurable lift, including dataset preparation, supervised and parameter-efficient fine-tuning, baseline evaluation, and deployment.
- Provides architectural direction and code-level guidance to existing .NET and SQL engineering teams responsible for backend services and data-layer integration with AI features.
- Defines and enforces LLMOps / MLOps practices: prompt and model versioning, evaluation harnesses, regression testing, latency and cost SLOs, and reproducible training pipelines.
- Implements observability for AI systems and makes the data actionable across token usage, latency, hallucination and refusal rates, contextual-grounding faithfulness, cost-per-request, and quality metrics.
- Builds and operates AI systems for audit-readiness - data lineage, prompt and model version traceability, decision logging, access controls, and evidence collection.
- Mentors fellow engineers, leads code review, contributes to architecture decision records, and helps shape the team's AI engineering standards.
- Partners with security and compliance to ensure AI systems meet data privacy, PII handling, prompt injection defense, and responsible-AI requirements throughout the model lifecycle.
Position Requirements- Bachelor's degree in Computer Science, Software Engineering, or a related field, or equivalent professional experience.
- 10+ years of professional software engineering experience.
- 2+ years building production AI/LLM features on a managed foundation-model platform.
- Demonstrable experience training and/or fine-tuning models - supervised fine-tuning, parameter-efficient fine-tuning (LoRA, QLoRA), or classical ML - including dataset preparation, evaluation, and deployment.
- Production experience with knowledge graphs - schema and ontology design, a graph database, and at least one graph query language (Cypher, SPARQL, or Gremlin).
- Demonstrable production experience in regulated environments. Compliance is a hard requirement for this role.
- 3+ years of production cloud experience including at least one managed AI service.
- Solid grounding in prompt engineering, RAG, embeddings, vector search, guardrails, contextual grounding, and LLM evaluation methodology.
- Ability to provide architectural direction and technical guidance to existing engineering teams; senior IC influence rather than line management.
- Strong testing discipline - unit, integration, and contract testing, plus AI-specific evaluation harnesses.
- Excellent written and verbal communication; ability to explain AI tradeoffs to non-technical, legal, and compliance stakeholders.
Compliance, Governance & TechnologiesThis role operates in a regulated environment. The Senior AI Developer is expected to understand how regulatory obligations apply to AI/ML systems specifically - training data, PII handling, model output controls, audit logging, evidence retention, and the limits regulation places on third-party model usage - and to produce the operational evidence that carries our AI capabilities through audits. Beyond these foundational compliance capabilities, we are seeking a developer with strong technical versatility across modern AI environments. Highly valued qualifications include:
- Hands-on experience with managed AI services across major cloud providers - for example Amazon Bedrock, Amazon SageMaker, Google Vertex AI, or Azure AI Foundry - is a plus. Familiarity across more than one provider is preferred.
- Production C# / .NET experience with ASP.NET Core and Entity Framework Core.
- Production SQL experience on Microsoft SQL Server and PostgreSQL - schema design, query tuning, indexing, and performance troubleshooting.
- Comfort working with on-premises database infrastructure and hybrid (on-prem / cloud) data architectures.
- Python proficiency for ML workflows.
- Production Infrastructure-as-Code experience (Terraform, CDK, CloudFormation, or Pulumi).
- Experience designing and consuming REST APIs, including modern authentication patterns (OAuth 2.0, OIDC, JWT).
- Broader machine learning experience: classical/predictive ML, deep learning frameworks, or experience with managed training platforms.
- GraphRAG patterns, entity resolution, and automated knowledge-graph construction from unstructured sources.
- Responsible-AI practices - bias evaluation, red-teaming, OWASP Top 10 for LLMs, prompt injection defense, NIST AI RMF, ISO/IEC 42001.
- Container experience (Docker, Kubernetes) and event-driven architecture experience.
- Experience supporting third-party audits - evidence collection and auditor-facing documentation.
- Open-source contributions, technical writing, conference talks, or research publications in AI/ML are a strong plus.
- Advanced degree (MS or PhD) in CS, ML, Statistics, or a related quantitative field is preferred.
Comprehensive Benefits- Medical & Health Savings: Choice of 3 medical tiers generously sponsored by the company, with a monthly $50-$100 employer HSA contribution based on plan type and dependent level.
- 100% Covered Dental & Vision: No premium costs for employees or dependents.
- 401(k) Matching: Generous 50% company match up to 6% of annual base salary.
- Diverse PTO Framework: Structured time off incorporating vacation, sick leave, mental health days, personal days, company holidays, and a flexible floating holiday.
- Income Protection & Family Leave: Full company sponsorship of Short-Term and Long-Term Disability (STD/LTD) alongside Paid Family Leave offerings.
