Role Overview
We are looking for a Sr. Technical Lead who combines deep hands-on engineering expertise with the ability to lead technical direction across teams. This role owns architecture and delivery quality for complex, cloud-native systems built on .NET Core and AWS, and is expected to champion Agentic AI adoption as a core part of the team's engineering culture.
Key Responsibilities
- Lead the technical design and hands-on development of complex, distributed microservices-based systems using .NET Core
- Own end-to-end architecture decisions for assigned components, balancing scalability, performance, security, and cost on AWS
- Drive adoption of Agentic AI and AI-augmented engineering practices across the team — set the tone for an AI-first development mindset
- Provide technical leadership across multiple squads/modules, ensuring consistency in design patterns, coding standards, and AWS usage
- Guide and review data engineering/integration flows using AWS Glue, EMR, DMS, and RDS/DynamoDB as applicable
- Act as the primary technical escalation point — solve ambiguous, high-complexity problems that span systems and teams
- Mentor Technical Leads and senior engineers; contribute to hiring and technical assessments
- Partner with client stakeholders (Wealth Management / Financial Services accounts) to translate business needs into robust technical solutions
- Champion engineering best practices: code quality, CI/CD, observability, and secure-by-design principles
Primary Skills — Must Have
- .NET Core (hands-on with the latest version — not just legacy .NET Framework experience)
- Microservices — proven ability to design AND build microservices-based systems end-to-end, not architecture-only exposure
- SQL Server — strong query writing, performance tuning, and schema design
- Entity Framework (EF Core) — practical, production-grade usage
- AWS Services, including hands-on work with (Any two of below listed AWS Services) :
- AWS Lambda / AWS CMI / AWS IAM / AWS Glue / AWS EMR / AWS DMS / AWS RDS / AWS DynamoDB / AWS CloudFront
- Working knowledge of, or strong interest in, Agentic AI / AI-assisted engineering tools and an active AI adoption mindset
- Strong problem-solving ability — comfortable working through ambiguous, complex technical challenges independently
Good to Have
- Prior experience in Wealth Management, Asset Management, Banking, or broader Financial Services domain
- Exposure to CI/CD pipelines, containerization (Docker/Kubernetes), and infrastructure-as-code
- AWS certification(s) — Solutions Architect, Developer Associate, or equivalent
Ideal Candidate Profile
- 11–15 years of overall experience, with demonstrated technical leadership across projects/teams
- A track record of owning architecture decisions and driving them through to production at scale
- Has led or strongly influenced adoption of new engineering practices (cloud, AI tooling, or modernization) within a team
