AI Developer, Senior Associate

The AI Engineer will play a key role in advancing AI-enabled capabilities across the Charles River Investment Management Solution and Alpha Platform. This individual will design, build, and scale production-grade AI systems, including copilots, agentic workflows, and automation services embedded directly into investment management processes.

To be successful, the candidate must be a hands-on engineer with strong experience in
LLMs, AI orchestration, and distributed systems
, capable of translating emerging AI patterns (e.g., RAG, agent frameworks, MCP integration) into secure, scalable enterprise solutions. This role requires close collaboration with product owners, architects, and domain teams to operationalize AI across client-facing and internal workflows.

• Enables Scalable AI Adoption:Builds reusable platforms and services that allow product teams to rapidly integrate AI without fragmentation

• Drives Business Impact:Embeds AI into front-to-back workflows, improving productivity, automation, and decision-making for clients

• Bridges Innovation and Production:Converts emerging AI technologies into secure, governed, production-ready capabilities

• Accelerates Time-to-Market:Enables faster delivery of high-value AI use cases through standardarchitectureand tooling

• Design, develop, and deploy
  AI-powered services
  , including copilots, agent-based workflows, and automation tools

• Build and integrate
  LLM-based solutions
  using orchestration frameworks and tool-calling patterns

• Implement
  RAG pipelines
  using enterprise data sources and vector databases

• Develop and integrate
  multi-agent systems
  using MCP servers, APIs, andA2
  
  Abased tooling

• Embed AI capabilities into
  core CRD and Alpha workflows
  across front, middle, and back-office processes

• Build reusable
  AI enablement platforms, SDKs, and shared services
  for product teams

• Integrate AI services with
  cloud platforms
  and enterprise systems

• Expose AI capabilities through
  API Management layers and event-driven architectures

• Ensure
  performance, scalability, and reliability
  of AI systems in production environments

• Implement
  monitoring, evaluation, and observability
  for AI models and pipelines

• Apply
  responsible AI practices
  (security, explainability, compliance, governance)

• Collaborate with product, architecture, data science, and UX teams to deliver end-to-end solutions

• Participate in agile development processes including sprint planning, code reviews, and retrospectives

• Strong expertise in
  LLMs, prompt engineering, and AI system design

• Experience building
  AI copilots, conversational interfaces, or agent-based systems

• Hands-on experience with
  RAG architectures, embeddings, and vector databases

• Familiarity with
  MCP frameworks, tool-calling patterns, and agent orchestration

• Experience with
  cloud-native AI services
  (Azure preferred) and distributed architectures

• Proficiency in
  Python
  and at least one additional language (Java, C#, or Type Script)

• Experience with
  API-driven architectures
  , microservices, and event streaming (Kafka, Event Hub)

• Knowledge of
  distributed caching
  (Redis,Hazelcast) and performance optimization patterns

• Strong software engineering fundamentals: testing, CI/CD, code quality, and design patterns

• Familiarity with
  AI governance, model risk management, and security best practices

• Ability to work across
  strategic and hands-on engineering tasks

• Strong collaboration and communication skills in cross-functional environments

• B.S. or M.S. in Computer Science, Engineering, Mathematics, or related field

• 0–3+ years of software engineering experience, with a focus on building scalable systems

• Experience delivering
  AI/ML-powered applications into…