Techknomatic
Engineering Lead / Solution Architect
- Compensation
- Not disclosed
- Location
- Pune
- Work setup
- Onsite
- Seniority
- Lead
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Architecture
- Posted
Skills
Must have
- Bachelor’s degree in Computer Science, Information Technology, Engineering, or equivalent practical experience.
- 8–12 years of software engineering experience, including at least 3 years in technical leadership or solution architecture.
- Demonstrated experience delivering and supporting production applications.
- Strong hands-on coding, debugging, system design, API architecture, and database design skills.
- Experience leading and mentoring developers, with practical knowledge of cloud deployment, CI/CD, and application security.
- Strong technical communication and documentation skills.
Nice to have
- Experience building SaaS products from initial development through production.
- Experience with multi-tenant applications and AI-powered products using RAG or LLM integrations.
- Familiarity with Supabase, PostgreSQL, Docker, DigitalOcean, Coolify, or similar deployment platforms.
- Experience governing AI-assisted development teams and improving observability, security testing, and performance.
- Experience building reusable shared services or platforms used by multiple products.
Full description
Role Overview
We are looking for a hands-on Engineering Lead / Solution Architect to lead the design, development, and production readiness of AI-powered and SaaS applications. The role combines solution architecture, technical decision-making, hands-on coding, code quality ownership, and developer mentoring. This is a technical leadership role rather than a project management position.
Key ResponsibilitiesSolution Architecture & Technical Design
- Design scalable, secure, maintainable SaaS and AI application architectures.
- Translate business requirements into technical designs and implementation plans.
- Define frontend, backend, API, database, and integration architecture; select appropriate technologies and infrastructure.
- Create architecture diagrams, technical specifications, and Architecture Decision Records (ADRs).
- Assess feasibility, scalability, performance, security, and technical risks before development begins.
Technical Leadership & Code Quality
- Lead and mentor a team of approximately 67 software developers, including junior engineers.
- Review code and pull requests; establish coding standards, Git workflows, and branch protection practices.
- Write production-quality code for complex or critical modules and resolve challenging technical issues.
- Identify design flaws, security vulnerabilities, performance issues, and technical debt.
- Guide developers on debugging, refactoring, testing, and maintainable software design.
AI-Assisted Development & AI Architecture
- Define standards for responsible AI-assisted coding using tools such as GitHub Copilot, Cursor, Claude Code, or similar tools.
- Review AI-generated code for correctness, security, maintainability, and performance.
- Establish safe practices for handling confidential information, source code, and credentials when using AI tools.
- Design and review AI-powered application architectures, including Retrieval-Augmented Generation (RAG) solutions.
- Guide document ingestion, embeddings, vector search, retrieval pipelines, and LLM API integrations.
- Evaluate AI response quality, latency, security, and operating costs; support integrations with ML or computer vision systems when required.
DevOps, Security & Production Readiness
- Define CI/CD pipelines, deployment standards, and development, staging, and production environments.
- Work with cloud platforms such as AWS, Azure, or DigitalOcean and container technologies such as Docker.
- Establish secure configuration and secrets management, logging, monitoring, alerting, and error tracking.
- Review authentication, authorization, database migrations, backups, disaster recovery, and rollback procedures.