Staff AI Platform Engineer

About SS&C Technologies

As a leading financial services and healthcare technology company based on revenue, SS&C is headquartered in Windsor, Connecticut, and has 27,000+ employees in 35 countries. Some 20,000 financial services and healthcare organizations, from the world's largest companies to small and mid-market firms, rely on SS&C for expertise, scale, and technology.

Staff AI Platform Engineer at SS&C Advent

SS&C Advent's financial solutions are going Agentic! We are expanding our team to achieve this transformation. Our top-tier products, covering the investment firm's front-to-back office, will be integral to this digital journey, which began with our cloud-native, award-winning Genesis Platform used globally.

We are actively building a next-generation Agentic AI Framework that integrates Model Context Protocol (MCP), Agent-to-Agent (A2A) communication, Machine Learning, and advanced orchestration on top of our enterprise big data platform.

We are seeking Staff AI Platform Engineers to join our R&D team. These engineers will be responsible for designing and implementing the core AI framework, ensuring its seamless integration with our big data infrastructure, and enabling scalable, intelligent, and autonomous data-driven systems.

Why You Will Love It Here!

• Flexibility: Hybrid Work Model & a Business Casual Dress Code, including jeans
• Your Future: 401 (k) Matching Program, Professional Development Reimbursement
• Work/Life Balance: Flexible Personal/Vacation Time Off, Sick Leave, Paid Holidays
• Your Wellbeing: Medical, Dental, Vision, Employee Assistance Program, Parental Leave
• Wide Ranging Perspectives: Committed to Celebrating the Variety of Backgrounds, Talents, and Experiences of Our Employees
• Training: Hands-On, Team-Customized, including SS&C University
• Extra Perks: Discounts on fitness clubs, travel, and more!

What You Will Get To Do

• Design and build a scalable Agentic AI framework on top of SS&C's data platform.
• Implement MCP- and A2A-based architectures for agent collaboration and orchestration.
• Integrate AI services with robust data pipelines (Airflow, Spark, Trino, StarRocks, DBT).
• Build APIs, SDKs, and tooling to empower other teams using the framework.
• Collaborate with platform and application teams to ensure secure, reliable, and multi-tenant deployment of AI agents.
• Evaluate cutting-edge agentic AI, LLM, and orchestration technologies, recommending adoption.
• Mentor other engineers and actively contribute to AI engineering best practices.

What You Will Bring

Core Skills (Must-Have)

• Strong programming skills in Python with 5+ years of experience.
• Proven experience with data engineering or distributed systems (Spark, Hive, Trino, StarRocks, DBT, Airflow, Kubernetes).
• Deep understanding of LLM-based systems and agent frameworks (LangChain, LlamaIndex, DSPy, OpenAI MCP, A2A).
• Hands-on experience with API design & integration (REST, GraphQL, gRPC).
• Knowledge of cloud infrastructure & container orchestration (Kubernetes, Docker).
• Strong understanding of IAM, security, and multi-tenancy in enterprise systems.
• Track record of building production-grade AI/data platforms.

Desired Skills (Nice-to-Have)

• Experience in Information Security.
• Experience with vector databases (pgvector, Pinecone, Weaviate, Milvus, Vespa).
• Familiarity with event-driven architectures (Kafka, Pulsar).
• Understanding of retrieval-augmented generation (RAG) patterns.
• Background in authorization/identity systems (ReBAC, RBAC, Zanzibar-style).
• Familiarity with observability (OpenTelemetry, DataHub, MLflow, Prometheus).
• Experience in enterprise AI governance (audit, lineage, compliance).
• Contributions to open-source AI frameworks (LangChain, OpenAI MCP, Hugging Face, etc.).

Key skills/competency

• AI Platform Engineering
• Python Programming
• Distributed Systems
• LLM-based Systems
• Agent Frameworks (LangChain, LlamaIndex, DSPy)
• API Design (REST, GraphQL, gRPC)
• Kubernetes & Docker
• Data Pipelines (Spark, Airflow)
• Security & Multi-tenancy
• Big Data Infrastructure