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State Street Corporation
Artificial Intelligence & Machine Learning Engineer (Multi-Agent Systems) - Assistant Vice President
State Street Corporation
Secunderabad•On-site•10-13 Yrs•Jun 16
Job description
Overview
We are seeking a Senior AI Engineer with deep expertise in multi-agent AI systems (agentic architectures) to design and deliver next-generation intelligent solutions at enterprise scale.
Responsibilities
- Multi-Agent System Design & Development
- Design and implement multi-agent architectures for enterprise use cases (decisioning systems, workflow automation, intelligent assistants).
- Develop cooperative, autonomous, and goal-driven agents with capabilities such as:
- Planning and reasoning
- Tool usage and API orchestration
- Memory management (short-term + long-term)
- Build agent ecosystems leveraging frameworks such as:
- LangChain / LangGraph
- AutoGen / CrewAI
- Semantic Kernel
- Custom orchestration frameworks
- AI/ML Solution Engineering
- Develop and deploy LLM-powered solutions, including:
- Retrieval-Augmented Generation (RAG)
- Fine-tuning / prompt engineering / evaluation pipelines
- Build scalable pipelines for:
- Data ingestion and embedding
- Vector search and knowledge retrieval
- Integrate AI with enterprise systems (trade platforms, risk engines, reporting systems)
- Enterprise-Grade Architecture
- Design solutions aligned with enterprise non-functional requirements:
- Security, auditability, explainability
- Scalability and high availability
- Cost optimization of LLM usage
- Implement observability for AI systems:
- Prompt tracing, agent behavior monitoring, hallucination detection
- Ensure compliance with regulatory standards (e.g., RBI, data localization, risk controls)
- Engineering Excellence
- Apply best practices in:
- CI/CD pipelines (e.g., GitHub Actions, Harness)
Qualifications
- Min 10+ years of software engineering experience with at least 3-5 years in AI/ML
- Proven experience in building production-grade AI systems in large enterprises
- Demonstrated progression from traditional engineering (Java/Python/Distributed Systems) to AI/ML
- Strong understanding of:
- Multi-agent architectures
- Autonomous systems & reasoning models
- Prompt engineering and LLM lifecycle
- OpenAI / Azure OpenAI / Anthropic / open-source LLMs
- Agent frameworks (LangChain, AutoGen, CrewAI, Semantic Kernel)
- RAG architectures, vector databases
- Model evaluation frameworks and prompt optimization
- Python ecosystem (PyTorch, TensorFlow, Hugging Face)
- Strong background in:
- Distributed systems
- Microservices architecture
- Languages: Python (primary), Java/Scala (preferred)
- API design and integration patterns
- Hands-on with AWS / Azure (preferred: AWS AI stack)
- Containers (Docker, Kubernetes/ECS)
- CI/CD tools (Harness, GitHub Actions)
- Monitoring tools (Prometheus, Grafana, OpenTelemetry)
- Familiarity with:
- Regulatory frameworks (RBI, Basel, data governance)
- Secure AI design and model risk management
- Exposure to graph-based workflows and knowledge graphs
- Architectural Thinking: Ability to design scalable, composable AI systems
- Problem Solving: Strong analytical mindset for complex enterprise use cases
- Innovation: Ability to translate emerging AI trends into practical solutions
- Execution Focus: Deliver high-quality, production-ready systems
- Stakeholder Engagement: Communicate effectively with business and senior leadership
Education
- Bachelor's or Master's degree in Computer Science, Engineering, AI/ML, or related field