About the Role
We're looking for an experienced Lead Engineer to drive the technical development of our data and intelligence infrastructure. You'll lead the intelligence platform engineering team—including data engineers and full-stack developers—to build scalable, production-grade systems that power AI-driven analysis and intelligence workflows.
This is a hands-on technical leadership role where you'll architect solutions, write code, set engineering standards, and build the culture that will scale our capabilities across the organization. You'll balance platform development with custom work, ensuring we build reusable systems while delivering immediate business value.
You'll work within the Data organization. The structure is flat and horizontal—strong collaboration across these teams is essential to success. You'll partner closely with data scientists on technical integration and with the business team on data sourcing, vendor relationships, and operational requirements.
This role is based in North America, but requires flexibility to collaborate with European team members during their business hours.
Responsibilities
Technical Leadership & Architecture
- Own technical roadmap and architecture for data processing and intelligence systems
- Design and implement scalable, maintainable systems that balance innovation with operational stability
- Make critical technical decisions on frameworks, patterns, and infrastructure
- Establish engineering best practices, code quality standards, and development workflows
- Review code, provide technical guidance, and maintain technical excellence across the team
- Balance platform development with custom/bespoke work to meet business needs
Hands-On Development
- Write production code across the full stack (Python backend, modern JavaScript/TypeScript frontend, data pipelines)
- Tackle the most challenging technical problems that require senior expertise
- Build and optimize API endpoints, authentication/authorization systems, and data processing workflows
- Implement LLM integration patterns and orchestration frameworks
- Develop agent integration interfaces and tools
- Ensure platform reliability, performance, scalability, and cost optimization
Team Leadership & Collaboration
- Lead and mentor a cross-functional team including data engineers, and full-stack developers distributed across US and EU time zones
- Set technical direction and prioritize work across platform development and business deliverables
- Organize workflows and processes to maximize team productivity and impact
- Foster a culture of experimentation, learning, and continuous improvement
- Recruit and retain top engineering talent as the team scales
- Create opportunities for continuous growth in technical skills and product thinking
Cross-Functional Integration
- Collaborate closely with data science team on technical integration, model deployment, and analytics capabilities
- Partner with business team on data procurement, vendor integration, and provisioning requirements
- Work effectively within a horizontal organizational structure where collaboration across teams is essential
- Collaborate with product managers and business stakeholders to translate requirements into technical solutions
- Work with DevSecOps teams to ensure secure, compliant operations
- Communicate technical concepts and trade-offs effectively to non-technical stakeholders
- Participate in Labs-wide planning and initiative prioritization alongside other technical leads
Product & Strategy
- Contribute to technical strategy and roadmap in collaboration with senior technical leadership
- Balance building reusable, scalable capabilities with delivering immediate business value
- Identify opportunities to consolidate and scale patterns from custom work
- Drive evolution from project-based development to product-based platform thinking
- Support the broader business by making engineering capabilities scalable and commercially viable
Qualifications
Required
- 8+ years of professional software engineering experience with 3+ years in technical leadership roles
- Strong full-stack development skills with Python (FastAPI, Django, or similar) and modern JavaScript/TypeScript (React, Next.js, or similar)
- Deep experience building and scaling API-driven platforms and microservices architectures
- Proven track record implementing RBAC, authentication, and multi-tenant systems
- Strong experience with GCP (Google Cloud Platform), Kubernetes, and PostgreSQL
- Experience with LLM integration, orchestration frameworks (LangChain, LlamaIndex, Mastra, or similar), and agentic AI systems
- Strong understanding of data processing pipelines, workflow orchestration, and ETL patterns
- Experience with containerization, orchestration, and modern DevOps practices
- Demonstrated ability to lead technical teams and mentor engineers at various levels
- Excellent communication skills and ability to work with cross-functional teams in flat organizational structures
- Comfortable working in fast-paced environments with evolving priorities
- Flexibility to collaborate with European team members during their business hours
- Experience managing distributed teams across time zones
Nice to Have
- Experience building platforms that serve both internal users and external APIs
- Background in media analytics, document processing, or intelligence/research platforms
- Familiarity with vector databases, semantic search, and RAG architectures
- Experience with Model Context Protocol (MCP) or similar agent integration patterns
- Knowledge of data science workflows and collaboration patterns between engineering and data science teams
- Experience working with data procurement, vendor management, or data provisioning operations
- Experience in consulting, professional services, or client-facing technical roles
- Contributions to open-source projects or technical community involvement
- Experience with real-time data processing and streaming architectures
What Success Looks Like
- Technical Excellence: Systems are reliable, scalable, and maintainable with clean architecture and minimal technical debt
- Team Performance: Engineering team is productive, collaborative, and continuously improving across time zones
- Cross-Team Collaboration: Seamless partnership with data science and business teams in a flat organizational structure
- Business Impact: Platform enables new capabilities and accelerates delivery of business value
- Velocity: Ability to rapidly develop and deploy new workflows as needs emerge
- Quality: High code quality, comprehensive testing, and robust monitoring/observability
- Scalability: Engineering capabilities support consultants, AI agents, and bespoke client projects across the organization
Why Join FGS Labs
- Work on cutting-edge AI and intelligence technology that powers strategic decision-making for global clients
- Lead technical development of production systems processing large-scale data
- Collaborate with world-class data scientists, engineers, and strategic communications experts
- Shape the technical culture and engineering practices of a growing team
- Significant autonomy and ownership over technical decisions and architecture
- Opportunity to work across the full stack and with modern AI/LLM technologies
- Thrive in a flat, collaborative organizational structure where your impact is direct and visible
- Competitive compensation and benefits
- Flexible work arrangements with hybrid/remote options
