Statestreet

Statestreet

GHR AI Engineer – Agentic Integrations (MCP / A2A / Python / APIs) AVP

Princeton, New Jersey

Sponsorship not specified$90k-$158kDetected 1 day ago
PythonReactBackend DevelopmentVector DatabasesRESTOAuthLLMsRAGAgentic AIAgileAuditingTest AutomationManual TestingCommunicationCollaboration

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odds of building a lasting career here

33Unrated
Cap-exempt (no lottery)0
Sponsors this role0
Entry-level history0
PERM / green-card track0
Lottery odds (Level III)83
Fits your clock70

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About the role

  • Salary Range: $90,000 - $157,500 Annual The range quoted above applies to the role in the primary location specified.
  • If the candidate would ultimately work outside of the primary location above, the applicable range could differ.
  • For a full overview, visit https://hrportal.ehr.com/statestreet/Home.

Responsibilities

  • Build and maintain MCP-based connectors that expose internal tools and data sources to AI agents in a consistent, secure way (tools/resources/prompts).
  • Implement agent-to-agent interaction patterns for multi-step workflows where agents coordinate across internal systems and external vendor agents.
  • Implement safe, reliable request routing patterns (timeouts, retries, circuit breakers, fallbacks) and error-handling standards. API & Backend Development (Python)
  • Develop lightweight Python services that broker requests between the React intranet and agent runtimes/tools.
  • Build and maintain REST APIs (and/or async workers) that support agent workflows, tool execution, and structured responses back to the UI.
  • Support data shaping and transformation (JSON, schemas, normalization) to make multi-source responses usable for employee-facing experiences. Grounding, Retrieval & Knowledge Enablement (as needed)
  • Assist in implementing retrieval/grounding patterns (document ingestion, chunking, embeddings, retrieval, citations) for intranet use cases.
  • Integrate knowledge sources (policies, HR content, FAQs, service catalogs) while respecting access controls and data classification requirements. Security, Compliance & Safe-by-Design Engineering
  • Implement least-privilege access for tools and connectors, secure secrets management, and strong logging/audit trails for tool invocation.
  • Grounding, Retrieval & Knowledge Enablement (as needed) • Assist in implementing retrieval/grounding patterns (document ingestion, chunking, embeddings, retrieval, citations) for intranet use cases. • Integrate knowledge sources (policies, HR content, FAQs, service catalogs) while respecting access controls and data classification requirements.

Nice to have

  • Experience & Competencies
  • 3-5 years of hands-on software engineering experience, with strong Python development skills.
  • Practical experience with APIs (REST), JSON/schema-driven payloads, and common auth patterns (OAuth/OIDC, token handling).
  • Familiarity with agentic concepts: tool/function calling, structured outputs, multi-step orchestration, and safe execution patterns.
  • Experience with MCP and/or agent-to-agent communication patterns strongly preferred.
  • Preferred / Nice to Have
  • Experience with RAG and vector databases
  • understanding of evaluation and quality testing for LLM systems.

Compensation

  • $90,000 - $157,500 Annual The range quoted above applies to the role in the primary location specified.
  • incentive compensation including eligibility for annual performance-based awards (excluding certain sales roles subject to sales incentive plans)

Company info

  • We keep our clients at the heart of everything we do, and smart, engaged employees are essential to our continued success.
  • We are committed to fostering an environment where every employee feels valued and empowered to reach their full potential.

Visa & Work Authorization

  • gin, ancestry, ethnicity, age, disability, genetic information, sex, sexual orientation, gender identity or expression, citizenship, marital status, domestic partnership or civil union status, familial status, military a
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This listing is sourced directly from Statestreet's careers page and normalized into a canonical job model.