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Dotmatics · 3 weeks ago

Senior Software Engineer - AI Agent Platform | Luma

Boston, MA

Full-time

Onsite

Senior Level, Lead/Staff

$145K/yr - $171K/yr

10+ years exp

Dotmatics is a company dedicated to integrating science, data, and decision-making to foster innovation in scientific research. They are seeking a Senior Full Stack AI Engineer to build and advance the Luma platform, focusing on AI agent workflows and scalable microservices. The role involves collaborating with a global team to develop cutting-edge AI/ML technology and deliver production-ready systems that enhance scientific intelligence.

BioinformaticsBiopharmaBiotechnologyCloud ComputingComputerData IntegrationData VisualizationLife SciencePharmaceuticalSaaS

H1B Sponsor Likely

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 behavior-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 behavior 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

Python 3.11+FastAPILangChain/LangGraphPostgreSQLReact & TypeScriptMicroservices designAI agent developmentClean ArchitectureDependency injectionCI/CD pipelinesMentoring

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

Benefits

Medical, Dental, Vision, Insurance

Health Spending Accounts

Wellness Benefits (Mental Health Apps and Fitness Perks)

Company-paid Life and Disability Insurance

401k Retirement Plan (with 4% company match; immediate vesting)

Flexible Time off Plan (for US exempt employees)

Company

Dotmatics

Dotmatics is an R&D scientific software connecting science, data, and decision-making. It is a sub-organization of Insightful Science.

Founded in 2005

Boston, Massachusetts, USA

501-1000 employees

https://www.dotmatics.com/

H1B Sponsorship

Dotmatics has a track record of offering H1B sponsorships. Please note that this does not guarantee sponsorship for this specific role. Below presents additional info for your reference. (Data Powered by US Department of Labor)

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2022 (3)