Sr. Software Engineer
About The Position
6sense is hiring a Senior AI Engineer to extend and operate its production agent and MCP platform. The role spans the full path from customer agents to 6sense data and actions, including APIs, tools, MCP, orchestration, context, evaluation, and security. The engineer will work closely with the Contextual Intelligence team, write production Python, own multi-month projects, support dependent teams and customers, and keep the platform current as agent tooling evolves. The position is hybrid in the San Francisco Bay Area or Austin, Texas. The role develops agents and orchestration, evolves APIs and tools for human and LLM consumers, scales the MCP layer, and integrates external clients, assistants, platforms, and partners. It also helps expose contextual intelligence through APIs, tools, and MCP; improves permission-aware retrieval and grounding; and builds evaluation, tracing, and usage analytics capabilities. Security, privacy, reliability, and trust are central responsibilities. The engineer will enforce tenant isolation and authorization, protect against prompt injection and data leakage, and establish runtime guardrails. The role also includes troubleshooting customer-reported production issues, supporting customer and partner discussions, documenting technical designs, reviewing code, mentoring engineers, participating in on-call and incident response, and evaluating emerging technologies. This is a hands-on engineering position rather than an architect-only role. MCP is one part of a broader platform strategy, and the systems are already in production supporting customers.
Requirements
- At least 5 years of experience building and operating production software systems.
- Strong distributed systems fundamentals, including idempotency, fault tolerance, backpressure, and failure recovery.
- At least 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; AWS is preferred.
- 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 communicating effectively with technical and non-technical audiences.
- Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
Nice To Haves
- Direct MCP experience is strongly preferred.
- 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.
Responsibilities
- Extend LangGraph orchestrators with typed state, conditional routing, subgraphs, checkpointing, durable execution, and human-in-the-loop workflows.
- Select and implement agent patterns such as routing, orchestrator-worker, plan-and-execute, reflection, and multi-agent handoffs based on business needs.
- Run agents headlessly through API-first and MCP-first architectures across in-app, chat, workflow, and partner surfaces.
- Build reusable components for state management, memory, tool-calling, and agent-to-agent delegation with scoped permissions.
- Evolve APIs and tools that enable agents and people to access 6sense data and take action.
- Optimize agent-facing tool design, including names, descriptions, schemas, response formats, error handling, and token efficiency.
- Redesign and scale the MCP layer for production workloads, including concurrency, tenant quotas, latency, caching, graceful degradation, backward compatibility, and emerging MCP capabilities.
- Onboard external MCP clients, AI assistants, agent platforms, and partners; develop integration guides and reference clients; define trust boundaries for third-party MCP server integrations.
- Strengthen platform reliability through idempotency, retries, rate limits, permissions, spend controls, and standards for tool contracts, versioning, and discovery.
- Partner with the Contextual Intelligence team to expose context through MCP, APIs, and tools, and define contracts for data, freshness, provenance, and access controls.
- Improve permission-aware retrieval and grounding through chunking, hybrid search, reranking, citations, context assembly, and memory management within token and latency constraints.
- Expand evaluation frameworks with golden datasets, accuracy and task-success metrics, regression testing, release gates, and context-quality measurements.
- Enhance tracing and usage analytics, reporting on task success, tool-call precision, groundedness, latency, and cost efficiency.
- Apply security considerations across tools, APIs, agents, and MCP; review code for vulnerabilities and security risks.
- Enforce tenant isolation, user-level authorization, and short-lived scoped credentials; protect against prompt injection, tool poisoning, excessive autonomy, and data leakage.
- Establish runtime guardrails for steps, tokens, execution time, and spend.
- Investigate and resolve customer-reported issues across agents, tools, models, and downstream systems.
- Participate in customer and partner technical discussions and support enablement teams with guidance, demonstrations, and documentation.
- Write design documents, evaluate trade-offs, conduct code reviews, mentor engineers, and participate in on-call and incident response rotations.
- Stay current with MCP, agent frameworks, and model capabilities; prototype promising technologies and share evidence-based recommendations.
Benefits
- Health coverage and generous health insurance coverage.
- Paid parental leave.
- Generous paid time off and holidays, including paid holidays and quarterly self-care days off.
- Life and disability insurance.
- 401(k) employer matching program.
- Stock options, subject to approval by 6sense’s board.
- Potential bonus program or commission plan.
- Equipment and support for working and connecting with teams at home or in an office.
- Learning and development initiatives, including access to LinkedIn Learning.
- Wellness education sessions and employee well-being activities.
- Wellness days and ERG-hosted events.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
