Dotmatics ยท 3 weeks ago
Senior AI Software Engineer - AI Agent Platform | Luma
United States
Full-time
Remote
Senior Level, Lead/Staff
10+ years expDotmatics is a company that intertwines science, data, and decision-making to drive innovation in scientific research. They are seeking a Senior Full Stack AI Engineer to build and advance the Luma platform, focusing on designing AI agent workflows and integrating cutting-edge AI/ML technology to enhance scientific data analysis.
BioinformaticsBiopharmaBiotechnologyCloud ComputingComputerData IntegrationData VisualizationLife SciencePharmaceuticalSaaS
No H1B
Hiring Manager
Michelle Laing MBA
Responsibilities
Design and implement AI agent workflows and tooling using LangChain/LangGraph, enabling AI models to plan actions, call tools, use APIs, search information, and reliably complete multi-step workflows
Build and maintain the tools, function interfaces, and system connectors that AI agents use to interact with databases, document stores, enterprise apps, and external APIs
Ensure AI agents operate safely, follow rules, respect permissions, and reliably execute within defined constraints
Lead and execute the design and implementation of core workflow orchestration and tooling features, including automated tasks and background processes
Build scalable FastAPI services with well-defined RESTful APIs and real-time streaming endpoints
Create modular, reusable service components with strong authentication, error handling, and pagination patterns
Develop and guide React frontend components for real-time interactions and data visualization
Implement multi-tenant architecture with secure isolation, resource boundaries, and long-term scalability
Provide technical guidance to other engineers during implementation, ensuring high-quality, maintainable solutions
Evaluate risk when implementing new features or refactoring, and propose safe rollout strategies
Clean Architecture principles with clear separation of concerns
Microservices design patterns including service discovery, API gateways, and interservice communication
Multi-tenancy architecture with schema-based isolation
Event-driven architecture with message queues and async processing
Subprocess isolation patterns for credential management and security boundaries
Influence architectural direction across teams, helping bring clarity and structure to ambiguous problems
Architect robust AI agent execution layers that ensure determinism, observability, and reliable stepwise execution
Write comprehensive automated tests using pytest and Jest, including integration and behaviour-driven tests
Implement structured logging, correlation IDs, and observability patterns to ensure system clarity and operability
Contribute to and improve CI/CD pipelines with automated testing, linting, and deployment workflows
Set up effective monitoring and alerting for production systems
Lead or support critical incident resolution with calm, context-driven decision-making
Drive platform-wide improvements in performance, reliability, and technical quality
Exercise independent judgment in methods, techniques, and evaluation criteria to ensure robust outcomes
Instrument AI agent systems with monitoring, tracing, and guardrails to ensure safe and predictable behaviour in production
Document architectural decisions, engineering patterns, and approaches that become long-term references for the team
Provide approach summaries and technical proposals before major implementations to ensure alignment with product and engineering partners
Participate in planning and estimation, applying deep technical judgment and strong product awareness
Mentor engineers, raise team capabilities, and guide others through complex engineering workflows (feature branches, PRs, ticket management)
Build relationships across engineering and product groups, influencing roadmaps and cross-team initiatives
Communicate risks, challenges, and opportunities proactively and clearly to stakeholders
Document and evangelize best practices for safe, reliable, and maintainable AI agent design
Qualification
Required
10+ years of professional software development experience, including significant experience owning and delivering large-scale technical systems
Ability to design durable architectures, independently lead high-impact engineering efforts, and mentor other engineers while maintaining exceptional coding standards
Expert-level Python 3.11+ with deep understanding of async/await, type hints, and modern Python best practices
Experience building AI agents using LangChain/LangGraph, including tool creation, step planning, function calling, retrieval workflows, and reliable agent-state management
FastAPI experience building production RESTful APIs, streaming endpoints (SSE), and async request handling
Strong PostgreSQL expertise (including performance tuning and schema design) and SQLAlchemy
Strong understanding of dependency injection, clean architecture, and functional programming concepts
Experience designing and scaling microservices in production environments
Ability to assess engineering risk, propose rollout strategies, and make high-impact architectural decisions
Experience building safe execution environments and guardrails for AI decision-making
React & TypeScript with modern hooks and state management patterns (Redux/Context)
Experience with Webpack Module Federation and micro-frontend architectures
Ability to design responsive, maintainable UI components using SCSS/CSS
Familiarity with Jest for robust frontend testing practices
LangChain & LangGraph expertise for building AI agent workflows, tool orchestration, and LLM integration
Proven experience building LLM-powered applications with frameworks like LangChain, LangGraph, or similar
Understanding of Retrieval-Augmented Generation (RAG) patterns and vector embeddings
Experience with agent orchestration, tool creation, and multi-step reasoning workflows
Familiarity with LLM serving endpoints (Databricks, OpenAI, Anthropic, or similar)
Knowledge of streaming responses, callback systems, and real-time feedback mechanisms
Understanding of Model Context Protocol (MCP) for tool integration
Preferred
Production Kubernetes experience with Helm charts and orchestration
Experience with Databricks or similar cloud data platforms
LangChain/LangGraph production implementations
Model Context Protocol (MCP) integration
React micro-frontends with module federation
Dapr or similar service mesh frameworks
Multi-tenant SaaS application development
Company
Dotmatics
Dotmatics is an R&D scientific software connecting science, data, and decision-making. It is a sub-organization of Insightful Science.
501-1000 employees
Funding
Current Stage
Late StageTotal Funding
unknownKey Investors
Insight Partners
2025-04-02Acquired
2017-11-01Private Equity
Leadership Team
Thomas Swalla
CEO & Board Director
Jerome Combes-Knoke
SVP of Corporate Strategy & Development
Recent News
2026-01-06
Company data provided by crunchbase