Technical Lead - MLOps

Position: Tech Lead (AI-based SaaS Product)

Location: On-site (Office-based)

Experience Required : 6+ years in software development (SaaS focus), with microservices, Java, AWS, and AI/ML exposure

About The Role

We are seeking a Tech Lead to drive the development of our AI-based SaaS product.
In this role, you will manage a team of highly skilled software developers and architects, ensuring the product's technical vision is clearly defined and executed.
You'll be the go-to person for system design, coding standards, and process optimization, while also providing hands-on technical leadership and mentorship to the team.

Key Responsibilities

Define and maintain the microservices architecture, ensuring high scalability, reliability, and maintainability.
Oversee AWS infrastructure (EC2, ECS/EKS, Lambda, S3, RDS), optimizing for cost, performance, and security.
Drive AI/ML feature development, collaborating with data scientists to design and deploy models using best practices in MLOps.
Establish and enforce coding standards, architectural principles, and best practices for the team.
Lead Agile ceremonies (sprint planning, retrospectives, daily stand-ups) ensuring timely and quality deliveries.
Manage resource allocation, risk mitigation, and technical debt for ongoing feature development.
Coordinate release planning and version control strategies, balancing new features with infrastructure improvements.
Collaborate with Product Management to develop and maintain product roadmaps and timelines.
Translate business requirements into actionable technical tasks, ensuring features are aligned with SaaS business metrics and goals.
Evaluate market trends and competitive positioning to inform product strategy and enhancements.
Directly manage and mentor software developers, architects, and other technical roles, fostering a culture of continuous learning and improvement.
Provide career development guidance and technical training to the team.
Drive recruiting efforts to expand and strengthen the development team with top talent.
Facilitate cross-functional communication with design, product, and business stakeholders.
Implement and oversee CI/CD pipelines to maintain high-quality, consistent builds and deployments.

Champion Infrastructure as Code (e.g , Terraform, CloudFormation) to automate and streamline environment setup and maintenance.

Ensure robust monitoring, logging, and alerting solutions are in place for rapid detection and resolution of issues.
Enforce security best practices for cloud and AI applications, including IAM, data encryption, and application security.
Ensure compliance with relevant standards and regulations, especially for AI systems handling sensitive data.
Stay updated on emerging technologies in AI, cloud, and microservices.
Identify opportunities to leverage new tools, frameworks, and practices that enhance the product's performance and differentiate it in the market.
Drive a culture of experimentation, prototyping, and data-driven decision-making.

Required Skills & Qualifications

6+ years of hands-on software development experience, preferably building SaaS products.
Proficiency in Java with a strong foundation in microservices design patterns (service mesh, API gateway, inter-service communication).
In-depth knowledge of AWS services (EC2, ECS/EKS, Lambda, S3, RDS) and their respective best practices.
Familiarity with AI/ML frameworks (TensorFlow, PyTorch, scikit-learn) and basic data engineering concepts.
Experience with container orchestration (Kubernetes or ECS).
Knowledge of CI/CD pipelines, using tools like Jenkins, GitLab CI, or CircleCI.
Expertise in Infrastructure as Code (Terraform, CloudFormation) and version control (Git).
Understanding of high availability, auto-scaling, and load balancing solutions.
Track record of delivering projects using Agile methodologies.
Ability to plan sprints, allocate resources, and manage project risks effectively.
Experience with backlog management tools (Jira, Trello, Asana, etc.
Demonstrated ability to lead and mentor teams, offering technical and career guidance.
Excellent stakeholder management and the ability to translate complex technical details into business-focused discussions.
Strong collaborative skills for working across cross-functional teams (Product, Operations, Data Science).
Aptitude for strategic thinking, balancing short-term product milestones with long-term technical sustainability.
Proven ability to handle high-pressure, fast-paced environments while maintaining quality and team morale.
Bias for action and the ability to quickly pivot based on new information or market feedback.

Preferred Qualifications

Experience building AI-based SaaS solutions in a start-up or fast-paced organizational environment.
Familiarity with serverless architectures (AWS Lambda, FaaS).
Knowledge of model deployment, model monitoring, and model retraining strategies (MLOps).
Understanding of SaaS metrics (ARR, MRR, churn, customer acquisition cost) and how technical decisions impact these metrics.