7 days ago
Responsibilities
- Define the platform-wide architecture, design patterns, and reference implementations for production agentic systems.
- Own architecture and standards for LangGraph, LangChain, LangSmith, agent orchestration, durable execution, tracing, evaluation, and developer tooling.
- Design tool and skill registries, MCP integrations, agent delegation contracts, safe execution, retries, rollback, permissions, and spend controls.
- Architect long-running workflows with checkpointing, replay, recovery, human approval, reliability metrics, and runtime limits.
- Own security, privacy, guardrails, PII protection, tenant isolation, authorization, threat modeling, red-team testing, and AI governance.
- Define model selection, routing, optimization, cost, latency, fallback, and multi-provider strategies.
- Influence multiple engineering teams through architecture reviews, RFCs, prototypes, technical standards, mentorship, and hiring support.
- Partner with Product, Data Science, Security, Legal, Infrastructure, IT, enterprise customers, and external technical communities.
Requirements
- 12+ years of experience building and operating production software, including deep distributed-systems experience with consistency, idempotency, backpressure, fault tolerance, and failure recovery.
- 4+ years of hands-on experience building production LLM-based systems and 2+ years shipping production agentic systems used by customers or internal users.
- Deep production experience with LangGraph, LangChain, and LangSmith, or equivalent agent orchestration and evaluation platforms.
- Strong Python development skills and demonstrated ability to build production-quality reference implementations.
- Production experience with retrieval and grounding at scale, including chunking, hybrid search, reranking, citation enforcement, and permission-aware retrieval.
- Experience owning AI evaluation practices using golden datasets, offline regression testing, LLM-as-judge evaluation, human calibration, and release gating.
- Hands-on experience with security, privacy, compliance, PII protection, tenant isolation, authorization boundaries, prompt-injection defenses, and data-leakage prevention in multi-tenant cloud environments, preferably AWS.
- Proven ability to influence architecture across multiple engineering teams without formal authority and communicate credibly with engineers, executives, security reviewers, and enterprise customers.
- Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
- Preferred qualifications include MCP server and client experience, agent interoperability, B2B GTM or RevTech platforms, Salesforce or marketing automation, fine-tuning or reinforcement learning, Kafka, Snowflake, Databricks, Spark, large-scale AI platforms, enterprise security reviews, and relevant open-source contributions, patents, publications, or talks.
Benefits
- Health coverage, paid parental leave, generous paid time off, holidays, quarterly self-care days, and stock options for full-time employees.
- Equipment and support to work and connect with teams from home or one of the company’s offices.
- Learning and development initiatives, including access to LinkedIn Learning.
- Quarterly wellness education sessions, wellness days, and ERG-hosted events.
Tech Stack
Categories
About 6sense
6sense is on a mission to revolutionize the way B2B organizations create revenue by predicting customers most likely to buy and recommending the best course of action to engage anonymous buying teams. 6sense Revenue AI is the only sales and marketing platform to unlock the ability to create, manage and convert high-quality pipeline to revenue. Customers report 2X increases in average contract value, 4X increases in win rate and 20-40% reduction in time to close deals. Know everything, do anything, with 6sense.