Online Generative Ai Engineer Jobs in Spring, TX

Job Summary:
Gene by Gene is dedicated to building a healthier and more connected world through precision health and genealogy services. They are seeking a Senior AI Developer to guide their AI/ML strategy and integrate generative-AI features into their products, providing architectural direction and code-level guidance to engineering teams.
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.
Qualifications:
Required:
• 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.
Preferred:
• 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.
Company:
Specializing in DNA-based ancestry & genealogy as Family Tree DNA. Founded in 2000, the company is headquartered in Houston, USA, with a team of 201-500 employees. The company is currently Growth Stage.