Principal Software Engineering Lead (AI)

Be a part of our success story. Launch offers talented and motivated people the opportunity to do the best work of their lives in a dynamic and growing company. Through competitive salaries, outstanding benefits, internal advancement opportunities, and recognized community involvement, you will have the chance to create a career you can be proud of. Your new trajectory starts here at Launch! The Role: Launch is actively seeking a visionary Solutions Architect / Principal Software Engineering Lead (AI) to design and deliver modern engineering and applied AI solutions across client engagements. This role blends deep hands‑on engineering, architectural leadership, AI system design, and client advisory. You will operate across system design, production‑grade engineering, multi‑agent architectures, cloud platform strategy, and the development of Launch’s AI practice. Responsibilities Include: Architecture & Technical Strategy
Define the technical direction for client engagements end-to-end: discovery, design, build, and production hardening.
Assess client technology ecosystems and identify high-impact opportunities for AI/ML integration.
Lead architecture reviews, design sessions, and technology selection across cross-functional stakeholder groups.
Translate ambiguous business problems into concrete engineering plans with clear scope, milestones, and risk callouts. AI Engineering & Delivery
Architect production agentic systems including multi-agent orchestration, agent harnesses, skill/tool composition, human-in-the-loop checkpoints, and inter-agent communication protocols (e.g., A2A, MCP).
Build and govern MCP server ecosystems: design, deploy, and secure Model Context Protocol integrations connecting AI agents to enterprise data sources, internal APIs, and third-party platforms.
Define agent skill and capability frameworks including reusable skill libraries, prompt engineering standards, and evaluation harnesses for consistent agent behavior across engagements.
Architect RAG pipelines, fine-tuning workflows, and model lifecycle infrastructure (training, serving, experiment tracking) as foundational components of agentic systems.
Integrate AI platforms and APIs (Azure OpenAI, Amazon Bedrock, Anthropic, Vertex AI) into production systems with enterprise-grade reliability, cost governance, and observability.
Establish AI-native development practices: embed tools such as Claude Code, Cursor, and GitHub Copilot into team workflows with standards for AI-assisted code review, test generation, and documentation.
Design evaluation and observability infrastructure including LLM eval frameworks, red-teaming, behavioral drift detection, and production monitoring across tool call chains, latency, and failure modes.
Apply responsible AI governance: define guardrails, access controls, and audit patterns for agentic workflows in enterprise environments including scope containment and escalation paths. Hands-On Engineering
Write production code and lead by example — this role requires someone who is still close to the code.
Design cloud-native architectures across multiple hyperscalers (AWS and Azure primarily) microservices, event-driven systems, serverless, and containerized workloads.
Define and implement infrastructure-as-code using tools such as Terraform, Pulumi, CloudFormation, or Bicep.
Design and optimize CI/CD pipelines, GitOps workflows, and container orchestration using Docker and Kubernetes.
Establish observability and reliability practices using tools such as Datadog, Prometheus, Grafana, CloudWatch, or Azure Monitor.
Drive security-by-design across the delivery lifecycle including IAM, network architecture, secrets management, and compliance automation. Leadership & Client Advisory
Lead engineering teams ranging from small squads to 10+ person delivery teams, scaling leadership approach to the needs of each engagement.
Mentor and develop engineers at all levels through code reviews, pairing, and design coaching.
Operate as a trusted advisor to client technical leadership and executive stakeholders. Communicate trade-offs clearly and build confidence.
Influence without direct authority — driving alignment across cross-functional teams through technical credibility and stakeholder management.
Lead discovery and requirements elicitation, surfacing the underlying business need beyond the stated request.
Produce clear written artifacts: technical proposals, architecture decision records, SOWs, and executive-level status communication.
Grow client relationships and identify follow-on opportunities through proposal contributions and delivery-driven account expansion.
Contribute to Launch's growth — practice development, thought leadership, and hiring. Qualifications: Must-Haves:
Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field.
10+ years in software engineering with demonstrated experience in architecture and technical leadership roles.
3+ years hands-on with AI/ML in production. Broad fluency across generative AI (LLMs, RAG, fine-tuning, agents), MLOps (model serving, pipelines, experiment tracking), and AI-integrated product development.
Consulting or client-facing delivery experience with a proven ability to integrate into client organizations and establish credibility with technical and executive stakeholders.
Full-stack engineering capability across frontend, backend, infrastructure, and data layers. Proficiency in multiple modern languages (e.g., Python, TypeScript/Node.js, C#/.NET, Java, or Go) with the ability to move between them as engagements require.
Multi-hyperscaler depth across AWS and Azure, including their respective AI/ML service ecosystems (Bedrock, SageMaker, Azure OpenAI, Azure ML). GCP experience is a plus.
Strong fundamentals in distributed systems, event-driven architecture, API design, and DevOps/platform engineering.
Experience leading engineering teams in agile delivery environments.
Business acumen with the ability to connect architecture decisions to cost, timeline, and organizational impact.
Executive presence and communication skills effective with both technical and non-technical audiences.
Proven ability to operate in ambiguous environments and adapt to diverse client cultures. Strong Differentiators
Experience contributing to the development of AI engineering practices, reusable frameworks, or internal accelerators within a consulting or enterprise environment.
Experience advising C-suite or VP-level stakeholders on AI strategy, investment prioritization, and organizational readiness.
Depth with agentic AI frameworks (LangChain, LangGraph, LangSmith, LlamaIndex, Semantic Kernel, CrewAI) and emerging standards like MCP (Model Context Protocol).
Experience with enterprise data platforms (Databricks, Snowflake, BigQuery) in the context of AI/ML workloads.
Cloud architecture certifications across AWS and Azure (AWS SA Professional, Azure Solutions Architect Expert).
Published writing, open-source contributions, or conference speaking that demonstrates thought leadership in AI or software architecture.
Domain depth in industries such as healthcare, financial services, retail, or public sector. Compensation & Benefits: As an employee at Launch, you will grow your skills and experience through a variety of exciting project work (across industries and technologies) with some of the top companies in the world! Our employees receive full benefits—medical, dental, vision, short-term disability, long-term disability, life insurance, and matched 401k. We also have an uncapped, take-what-you-need PTO policy. The anticipated base wage range for this role is $190,000 to $230,000. Education and experience will be highly considered, and we are happy to discuss your wage expectations in more detail throughout our internal interview process.