AI Agent Engineer

Client Delivery

• Design and build production AI agent systems for clients across industries, from scoping through deployment and iteration
• Lead technical discovery workshops to identify high-value automation opportunities in client workflows
• Select and integrate the right agent frameworks, platforms, and models for each engagement (LangChain, LangGraph, CrewAI, Claude Managed Agents, custom orchestration, and others as the landscape evolves)
• Design human-in-the-loop workflows, approval gates, and escalation paths so agent systems operate safely in client environments, especially in regulated or risk-sensitive industries
• Translate complex AI capabilities into clear, actionable recommendations for non-technical stakeholders
• Collaborate with LaunchPad Lab's engineering and design teams to deliver end-to-end solutions

Internal Agent Strategy & Operations

• Own LaunchPad Lab's internal agent automation roadmap
• Identify processes ripe for agent-driven improvement and build the solutions
• Evaluate new agent frameworks, platforms, and tooling
• Develop reusable agent architectures, prompt libraries, and patterns that accelerate delivery across the consultancy
• Contribute to the AI practice's positioning, thought leadership, and go-to-market efforts with technical credibility
• Mentor other engineers on AI patterns, tools, and best practices as the practice grows

Requirements

• Must Have:
• 2+ years of professional software engineering experience with strong fundamentals
• 2+ years of hands-on experience building AI agent systems, including autonomous or semi-autonomous agents deployed in production environments
• Deep working knowledge of agent orchestration frameworks (LangChain, LangGraph, CrewAI, LlamaIndex, Claude Managed Agents, or equivalent)
• You should have opinions about their tradeoffs
• Experience with agent design patterns including prompt engineering, RAG architectures, tool/function calling, agent memory management, and evaluation frameworks
• Demonstrated ability to lead client-facing technical conversations, translate business problems into technical solutions, and present to senior stakeholders

Nice to Have

• Consulting or agency experience delivering technical projects for external clients
• Familiarity with infrastructure for AI workloads: vector databases (Pinecone, Weaviate, pgvector), cloud platforms (AWS, Azure, or GCP), and observability tools (LangSmith, PostHog, or OpenTelemetry)
• MLOps experience: comfortable with LLM monitoring, agent observability, eval design, and guardrail implementation to keep agent systems reliable and safe in production
• Experience building internal tools or automations that improved operational efficiency
• Hands-on experience with workflow automation and AI agent platforms such as Workato, Cassidy AI, n8n, Claude, or Claude Managed Agents

Benefits

• Variety and impact: You will work across industries and problem spaces, not a single product backlog
• Real ownership: You will shape the AI practice and the internal playbook from the ground up
• Senior, lean culture: Small teams of experienced engineers. Fully remote with a collaborative, low-ego team that has been building software together for over a decade
• Compensation:
• This role is available as a full-time position or a long-term contract engagement
• We're open to structuring it around the right person
• Salary Range: $125,000-175,000 (for full-time role)
• Benefits:
• Health Insurance (company pays 100% of employee PPO premium)
• Dental Insurance (company pays 100% of employee premium)
• Vision Insurance (company pays 100% of premium)
• 401(k) with up to 4% company match
• $1,000 annual conference budget
• Flexible work and vacation schedule