Developer

AI Developer Who we are looking for 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. Why this role is important to us 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 standard architecture and tooling What you will be responsible for 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, and A2A based 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 What we value 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 TypeScript) 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 Education & Preferred Qualifications B.S. or M.S. in Computer Science, Engineering, Mathematics, or related field Preferred: Experience in investment management, trading systems, or financial data platforms Experience with AI agent #J-18808-Ljbffr