You will lead by example, guide architectural decisions, mentor engineers, and champion strong engineering practices while responsibly introducing emerging technologies such as GenAI into production systems.
Key Responsibilities:
- Provide technical leadership to an agile, cross-functional development team
- Define and communicate technical vision across multiple workstreams
- Design scalable, secure, and resilient architectures for search and AI-powered systems
- Make architectural trade-offs balancing performance, cost, reliability, and security
- Collaborate with other Tech Leads to plan technical spikes and long-term technical strategy beyond sprint scope
- Identify technical risks early and lead mitigation strategies
- Architect systems leveraging:
LLM integrations (e.g., Azure OpenAI, OpenAI APIs, etc.)
Retrieval-Augmented Generation (RAG)
Semantic search and vector databases
- Establish guardrails for AI systems including:
Evaluation frameworks
Observability and monitoring
Data governance and security considerations
- Guide the team from experimentation prototype production-ready AI systems
- Evaluate emerging AI technologies and assess suitability for public sector use cases
- Champion Agile technical practices (TDD, pair programming, refactoring, CI/CD)
- Lead DevOps adoption including build, release automation, and infrastructure improvements
- Oversee automated testing strategy (unit, integration, performance)
- Lead resolution of technical blockers and retrospective improvements
- Ensure engineering standards are upheld across the team
- Work closely with Product Owners and Business Analysts to priorities business stories and technical investments
- Collaborate with UX Designers for feasibility studies and solution estimation
- Partner with Delivery Managers on long-term planning, system integrations, and resource forecasting
- Represent the development team in governance and stakeholder meetings
- Mentor and coach engineers to grow both technically and professionally
Qualifications:
- 5–7+ years of experience in web application development
- Proven experience leading agile development teams
- Strong hands-on experience with:
Node.js, TypeScript
Cloud platforms (Azure, AWS, GCP)
SQL & NoSQL databases
CI/CD pipelines
DevOps practices
- Designed or led systems involving:
Search engines (crawl, index, ranking, relevance tuning)
Semantic search or vector search
RAG architectures
- Production experience integrating LLMs into applications
- Experience managing AI-related trade-offs:
Latency vs cost
Accuracy vs hallucination risks
Prompt engineering strategies
Model evaluation methodologies
- Understanding of AI system governance, security, and responsible AI practices
- Strong coaching and mentoring capabilities
- Comfortable leading technical discussions and influencing stakeholders
- Proactive self-starter with strong ownership mindset
- Passionate about continuous improvement
- Curious about emerging technologies and willing to experiment responsibly
- Strong communication and stakeholder management skills
- Meticulous attention to quality and engineering standard