Sr. Software Engineer

San Francisco · USD 179,400-248,120 · 2+ years experience · Hybrid · Posted Oct 15, 2026

At a glance

6sense is looking for a Senior AI Engineer for its Agentic Platform to build more capable agents, strengthen the API and tool layer, and expand an ecosystem for external agents, clients, and partners.
This role involves working across the full path from a customer's agent to 6sense data and actions, including APIs, tools, MCP, orchestration, context, evaluation, and security.
The person in this role will partner closely with the contextual intelligence team, write production Python daily, own multi-month projects, and keep the platform current.

Extend LangGraph orchestrators with typed state, conditional routing, subgraphs, checkpointing, durable execution, and human-in-the-loop workflows.
Select and implement routing, orchestrator-worker, plan-and-execute, reflection, and multi-agent handoff patterns based on business needs.
Run agents headless through API-first and MCP-first architectures across in-app, chat, workflow, and partner surfaces from a shared core.
Build and maintain reusable components for state management, memory, tool-calling, and agent-to-agent delegation with scoped permissions.
Evolve the APIs and tools agents use to access 6sense data and take action for both human and LLM consumers.
Optimize tool design for agent success, including naming, descriptions, schemas, response formats, error handling, and token efficiency.
Re-design and scale the MCP layer for production workloads, including concurrency, per-tenant quotas, latency budgets, caching, graceful degradation, backward compatibility, and adoption of emerging MCP capabilities.
Onboard external MCP clients, AI assistants, agent platforms, and partners, develop integration guides and reference clients, and define trust boundaries.
Strengthen platform reliability through idempotency, retries, rate limits, permissions, spend controls, and standards for tool contracts, versioning, and discovery.
Investigate and resolve customer-reported issues across agents, tools, models, and downstream systems.

5+ years of experience building and operating production software systems, with strong distributed systems fundamentals including idempotency, fault tolerance, backpressure, and failure recovery.
2+ years of experience building production LLM-powered systems, including customer-facing agents.
Strong Python development skills and production experience with LangGraph or a comparable orchestration framework.
Experience designing APIs and tool interfaces for LLM consumers, including schemas, descriptions, error handling, and tool selection optimization.
Experience scaling customer- or partner-facing platforms, including authentication, rate limiting, versioning, and backward compatibility.
Hands-on experience with retrieval, grounding, and LLM evaluation frameworks.
Experience building multi-tenant, security-sensitive cloud systems, including authorization boundaries and data leakage prevention.
Proven ability to debug production issues across distributed services and support customers directly or through support and solutions teams.
Demonstrated success leading multi-month, cross-functional initiatives with minimal oversight and strong communication skills across technical and non-technical audiences.
Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.

Experience building or operating MCP servers in production or contributing to MCP open-source projects.
Experience serving context to agents from signals, entity data, knowledge graphs, or enterprise data platforms.
Experience integrating with external agent platforms, AI assistants, or agent interoperability protocols.
Familiarity with B2B go-to-market platforms, RevTech, CRM systems, or intent-data platforms.
Experience with model routing, caching, cost optimization, and latency optimization.
Experience with Kafka, Snowflake, Databricks, Spark, or similar data platforms.