About TheRole
As a CBRESoftware Engineer Principal, you will own and lead the Forward DeployedEngineering (FDE) pod operating under a metered-funding incubation model. Thisis a builder-first, hands-on leadership role (40% time spent directlyarchitecting and coding) for someone who thrives in ambiguity, has a strongbias for action, and combines deep full-stack and enterprise AI engineeringexpertise with business and product sense. The ideal candidate will manage andgrow the attached FDE pod, work directly with business stakeholders to scopeand build solutions, and drive rapid prototype-to-demo cycles that unlock newenterprise value.
What You'llDo
- Leadand manage the Forward Deployed Engineering (FDE) pod operating under ametered-funding incubation model, owning delivery outcomes and teamperformance.
- Operateas a hands-on architect (40% of time) — personally designing, building, and shipping enterprise-grade, full-stack AIsolutions alongside the team.
- Partnerdirectly with business and product stakeholders to translate ambiguous,open-ended problems into scoped, fundable incubation initiatives.
- Drivea rapid build-demo-iterate cadence — whiteboard concepts, build workingprototypes, and demo to clients/stakeholders on tight cycles.
- Architectand implement enterprise-grade AI systems, including multi-agent workflows, RAGpipelines, and LLM-based solutions integrated into real client environments.
- Buildconnectors and secure data pipelines between client/business systems and AIplatforms, ensuring scalability and reliability in production.
- Recruit,mentor, and grow a high-performing engineering team, instilling a builder-firstculture and strong technical bar.
- Actas the critical link between field/incubation learnings and the broader productand engineering roadmap, surfacing insights that shape strategic direction.
- Manageincubation funding and resourcing decisions in a metered-funding model —balancing speed of delivery against business case justification.
- Leadexecutive-level demos and readouts, articulating technical solutions andbusiness value clearly to both technical and non-technical audiences.
What You'llNeed
- Bachelor'sor Master's degree in Computer Science, Engineering, or a related technicalfield.
- 8+years of progressive experience in software engineering, applied AI/ML, orfull-stack architecture, including direct people-management or pod-leadershipexperience.
- Priorexperience in a customer-facing, forward-deployed, or consulting/implementationcapacity is strongly preferred.
- Backgroundfrom a top-tier technology company (FAANG/equivalent), high-growth productorganization, or premier consulting firm is strongly preferred.
TechnicalSkills
- Full-StackEngineering: Expert-level proficiency across the stack — backend, frontend,APIs, and data pipelines — with hands-on coding ability (Python,TypeScript/Node.js, Java, or equivalent).
- Enterprise-GradeAI: Demonstrable depth in LLMs, multi-agent systems, RAG, embeddings, vectordatabases, and prompt engineering, with experience deploying these inproduction enterprise environments.
- Cloud& MLOps: Hands-on experience with AWS/GCP/Azure and MLOps tooling fordeploying and scaling AI systems.
- API& Systems Integration: Experience designing and integrating APIs andconnectors with enterprise systems (e.g., Salesforce, ServiceNow, Palantir).
- Architecture& Delivery: Strong grasp of SDLC, agile methodologies, and pragmaticarchitecture decision-making in fast-moving, ambiguous environments.
Leadership andBusiness Acumen
- Provenbuilder mindset — prefers shipping working solutions over lengthy planningcycles; strong bias for action.
- Demonstratedability to build, mentor, and scale high-performing engineering teams from theground up.
- Strongproduct and business sense — able to evaluate technical decisions through thelens of business value and ROI.
- Comfortableoperating with significant ambiguity, incomplete requirements, and evolvingscope.
- Experienceoperating in or managing metered-funding, incubation, or innovation-lab styleengagement models is a strong plus.
Good To Have
- AgenticAI hands-on experience — designing and deploying autonomous, proactivemulti-agent systems in production.
- Familiaritywith containerization technologies (Docker, Kubernetes).
- Priorexperience in commercial real estate or adjacent industries.
- Experiencepresenting to and influencing C-suite or senior executive stakeholders.
