Manager, Software Development Engineering, CoCounsel FDE

About the role

Lead and support multiple cross-functional Forward Deployed Engineering project teams, ensuring efficient and effective execution while resolving issues as they arise
Architect and guide the design of scalable, secure AI/software solutions, applying deep knowledge of software and AI system architecture to complex, end-to-end AI/ML development across the software development lifecycle
Drive innovation by evaluating and adopting emerging AI methodologies, influencing enterprise-wide MLOps and LLMOps practices, and setting strategy for testing, AI monitoring, and debugging at the platform level
Manage and develop talent through hiring, performance management, coaching, and mentoring of engineers, fostering a culture of technical growth and high performance
Translate business needs into AI solutions by communicating and coordinating with project teams, partners, and stakeholders, and by championing thought leadership that promotes reusable, consistent AI frameworks and patterns
Own technical delivery across multiple projects and products—including large-scale AI/ML initiatives—by removing impediments, guiding project leads, and managing budgets where applicable
Build a customer-aware, high-performing team culture, ensuring close collaboration with Product, Project Management, and Technical Operations to deliver impactful, prioritized work

Responsibilities

• Lead and support multiple cross-functional Forward Deployed Engineering project teams, ensuring efficient and effective execution while resolving issues as they arise
• Architect and guide the design of scalable, secure AI/software solutions, applying deep knowledge of software and AI system architecture to complex, end-to-end AI/ML development across the software development lifecycle
• Drive innovation by evaluating and adopting emerging AI methodologies, influencing enterprise-wide MLOps and LLMOps practices, and setting strategy for testing, AI monitoring, and debugging at the platform level
• Manage and develop talent through hiring, performance management, coaching, and mentoring of engineers, fostering a culture of technical growth and high performance
• Translate business needs into AI solutions by communicating and coordinating with project teams, partners, and stakeholders, and by championing thought leadership that promotes reusable, consistent AI frameworks and patterns
• Own technical delivery across multiple projects and products—including large-scale AI/ML initiatives—by removing impediments, guiding project leads, and managing budgets where applicable
• Build a customer-aware, high-performing team culture, ensuring close collaboration with Product, Project Management, and Technical Operations to deliver impactful, prioritized work

Requirements

• 10+ years in software/solutions engineering, including 2+ years in a formal or informal people-management or team-lead capacity, while remaining technically hands-on rather than purely administrative
• Team leadership experience — you've led and grew a team of forward-deployed, field, or solutions engineers, with direct accountability for hiring, performance management, career development, and team structure
• Sustained customer-facing experience — running discovery sessions, presenting architecture, defending technical decisions, and building trust with both technical and non-technical stakeholders (GCs, IT leaders, innovation teams)
• A track record of scoping, building, and demoing rapid POCs and pilots against ambiguous or evolving requirements, and turning what you learn into repeatable patterns your team can execute on
• Strong Python development skills, plus hands-on AWS expertise (Bedrock AgentCore, CDK, EKS, ECR) and ownership of CI/CD pipelines (Docker, SQL/Flyway migrations, Cumulus or similar enterprise deployment platforms)
• Direct ownership of building and deploying LLM-powered agents (Anthropic Claude or similar) — from requirements gathering and solution design through implementation, integration, and production hand-off — including backend, frontend, agent guardrails/security design, evaluation frameworks and scorecard-based quality testing, and production observability (e.g., Datadog), and infra
• Comfort operating at the intersection of Product, Engineering, Sales, and Customer Success, translating customer-specific technical work into structured feedback that shapes the core CoCounsel product roadmap

Qualifications

• Familiarity with the legal industry or legal tech (e.g., document review, contract lifecycle, legal research) is a strong plus, given the domain-specific nature of customer requirements

Skills

• Technical leadership and people management skills
• Deep knowledge of software and AI system architecture
• Experience with AWS and CI/CD pipelines
• Hands-on experience with LLM-powered agents
• Ability to translate business needs into scalable AI solutions
• Strong communication and stakeholder management skills

Benefits

Hybrid Work Model
Flexibility & Work-Life Balance
Career Development and Growth
Industry Competitive Benefits
Culture
Social Impact