Role Proficiency:
Act creatively to develop applications by selecting appropriate technical options optimizing application development maintenance and performance by employing design patterns and reusing proven solutions. Account for others' developmental activities; assisting Project Manager in day to day project execution.
Outcomes:
Interpret the application feature and component designs to develop the same in accordance with specifications. Code debug test document and communicate product component and feature development stages. Validate results with user representatives integrating and commissions the overall solution. Select and create appropriate technical options for development such as reusing improving or reconfiguration of existing components while creating own solutions for new contexts Optimises efficiency cost and quality. Influence and improve customer satisfaction Influence and improve employee engagement within the project teams Set FAST goals for self/team; provide feedback to FAST goals of team membersMeasures of Outcomes:
Adherence to engineering process and standards (coding standards) Adherence to project schedule / timelines Number of technical issues uncovered during the execution of the project Number of defects in the code Number of defects post delivery Number of non compliance issues Percent of voluntary attrition On time completion of mandatory compliance trainingsOutputs Expected:
Code:
Code as per the design Define coding standardstemplates and checklists Review code – for team and peers
Documentation:
checklists
guidelines
standards for design/process/development Create/review deliverable documents. Design documentation
requirements
test cases and results
Configure:
Test:
scenarios and execution Review test plan created by testing team Provide clarifications to the testing team
Domain relevance:
Manage Project:
Manage Defects:
Estimate:
Manage knowledge:
share point
libraries and client universities Review the reusable documents created by the team
Release:
Design:
LLD
SAD)/architecture for applications
features business components and data models
Interface with Customer:
Manage Team:
opportunities
etc Ensure team members are upskilled Ensure team is engaged in project Proactively identify attrition risks and work with BSE on retention measures
Certifications:
Skill Examples:
Explain and communicate the design / development to the customer Perform and evaluate test results against product specifications Break down complex problems into logical components Develop user interfaces business software components Use data models Estimate time and effort resources required for developing / debugging features / components Perform and evaluate test in the customer or target environments Make quick decisions on technical/project related challenges Manage a team mentor and handle people related issues in team Have the ability to maintain high motivation levels and positive dynamics within the team. Interface with other teams designers and other parallel practices Set goals for self and team. Provide feedback for team members Create and articulate impactful technical presentations Follow high level of business etiquette in emails and other business communication Drive conference calls with customers and answer customer questions Proactively ask for and offer help Ability to work under pressure determine dependencies risks facilitate planning handling multiple tasks. Build confidence with customers by meeting the deliverables timely with a quality product. Estimate time and effort of resources required for developing / debugging features / componentsKnowledge Examples:
Appropriate software programs / modules Functional & technical designing Programming languages – proficient in multiple skill clusters DBMS Operating Systems and software platforms Software Development Life Cycle Agile – Scrum or Kanban Methods Integrated development environment (IDE) Rapid application development (RAD) Modelling technology and languages Interface definition languages (IDL) Broad knowledge of customer domain and deep knowledge of sub domain where problem is solvedAdditional Comments: Job Title: AI Tech Lead
Experience: 4 to 7 years
Location: Chennai / Thiruvananthapuram (TVM) / Kochi
Employment Type: Full-Time
We are seeking a highly skilled AI Tech Lead to design, develop, and lead the deployment of end-to-end AI solutions on AWS. This role requires deep technical expertise in cloud infrastructure, AWS AI services, NLP, AIOps, and building secure, scalable, and production-ready systems. The ideal candidate will have experience in leading cross-functional teams and delivering high-impact AI projects aligned with business goals.
Key Responsibilities Cloud Infrastructure & DeploymentDesign scalable, secure AI infrastructure using AWS services: EC2, VPC, RDS, DynamoDB, SageMaker, Bedrock, CloudWatch.
Implement Infrastructure-as-Code (IaC) using Terraform and manage CI/CD pipelines for seamless deployment.
Ensure high availability, fault tolerance, and operational excellence of cloud-based AI solutions.
AI Project LeadershipTranslate business objectives into technical AI solutions and success metrics.
Lead the end-to-end development lifecycle: data ingestion, modeling, deployment, and monitoring.
Define and enforce AI architecture standards and best practices.
Model Development & Responsible AIGuide selection and implementation of AI/ML models, including bias detection, explainability, and governance frameworks.
Use AWS tools to optimize model performance, cost-efficiency, and scalability.
Security & ComplianceEnforce security best practices including IAM roles, encryption, and secure access policies.
Ensure compliance with data governance and industry standards (e.g., GDPR, HIPAA).
Team Leadership & CollaborationLead and mentor a team of ML engineers, software developers, analysts, and DevOps engineers.
Conduct performance reviews and provide strategic direction to the AI engineering team.
Foster cross-functional collaboration and effective communication across teams.
Monitoring & MaintenanceImplement model monitoring, drift detection, and ongoing reliability measures in production.
Mandatory Skills & Experience4–7 years of experience in AI/ML development and deployment.
Proven track record of leading AI/ML projects on AWS.
Strong expertise in AWS services: EC2, SageMaker, Bedrock, RDS, VPC, DynamoDB, CloudWatch.
Proficiency in Python, Terraform, Docker, and Git.
Solid understanding of CI/CD, MLOps, and cloud security.
Experience with responsible AI practices: fairness, bias mitigation, explainability.