Role Proficiency:

Independently develops error free code with high quality validation of applications guides other developers and assists Lead 1 – Software Engineering

Outcomes:

     Understand and provide input to the application/feature/component designs; developing the same in accordance with user stories/requirements.      Code debug test document and communicate product/component/features at development stages.      Select appropriate technical options for development such as reusing improving or reconfiguration of existing components.      Optimise efficiency cost and quality by identifying opportunities for automation/process improvements and agile delivery models      Mentor Developer 1 – Software Engineering and Developer 2 – Software Engineering to effectively perform in their roles      Identify the problem patterns and improve the technical design of the application/system      Proactively identify issues/defects/flaws in module/requirement implementation       Assists Lead 1 – Software Engineering on Technical design. Review activities and begin demonstrating Lead 1 capabilities in making technical decisions

Measures of Outcomes:

     Adherence to engineering process and standards (coding standards)      Adherence to schedule / timelines      Adhere to SLAs where applicable      Number of defects post delivery      Number of non-compliance issues      Reduction of reoccurrence of known defects      Quick turnaround of production bugs      Meet the defined productivity standards for project      Number of reusable components created   Completion of applicable technical/domain certifications Completion of all mandatory training requirements

Outputs Expected:

Code:

Develop code independently for the above

Configure:

Implement and monitor configuration process

Test:

Create and review unit test cases
scenarios and execution

Domain relevance:

Develop features and components with good understanding of the business problem being addressed for the client

Manage Project:

Manage module level activities

Manage Defects:

Perform defect RCA and mitigation

Estimate:

Estimate time
effort
resource dependence for one's own work and others' work
including modules

Document:

Create documentation for own work as well as perform peer review of documentation of others' work

Manage knowledge:

Consume and contribute to project related documents
share point
libraries and client universities

Status Reporting:

Report status of tasks assigned Comply with project related reporting standards/process

Release:

Execute release process

Design:

LLD for multiple components

Mentoring:

Mentor juniors on the team Set FAST goals and provide feedback to FAST goals of mentees

Skill Examples:

Explain and communicate the design / development to the customer Perform and evaluate test results against product specifications Develop user interfaces business software components and embedded software components 5 Manage and guarantee high levels of cohesion and quality6 Use data models Estimate effort and resources required for developing / debugging features / components Perform and evaluate test in the customer or target environment Team Player Good written and verbal communication abilities Proactively ask for help and offer help

Knowledge Examples:

     Appropriate software programs / modules      Technical designing      Programming languages      DBMS      Operating Systems and software platforms      Integrated development environment (IDE)      Agile methods Knowledge of customer domain and sub domain where problem is solved

Additional Comments:

Key Responsibilities: • Design, develop, and implement AI and machine learning models and algorithms tailored to solve specific business challenges. • Collaborate with software engineers, and other stakeholders to integrate AI solutions into existing applications and platforms. • Analyze large datasets to identify patterns and insights that can drive model development and optimization. • Optimize and fine-tune machine learning models for performance, scalability, and efficiency. • Stay current with the latest AI and machine learning research, tools, and techniques to ensure our solutions are cutting-edge. • Develop and maintain documentation for AI models, algorithms, and workflows. • Participate in code reviews, provide constructive feedback, and ensure best practices in AI and software development are followed. • Assist in troubleshooting and resolving issues related to AI models and systems in production environments. • Collaborate with product managers and stakeholders to understand business requirements and translate them into technical specifications for AI development. Qualifications: • Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field. • 3-6 years of experience in AI development, machine learning, or a related field. • Strong programming skills in at least one of the following languages Python, R, Java, or C++, with the preferred language being Python • Proficiency with machine learning frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, or Keras. • Experience with data preprocessing, feature engineering, and model evaluation techniques. • Familiarity with cloud platforms and services (particularly MS Azure) for deploying AI models. • Strong problem-solving skills and the ability to work independently and collaboratively in a team environment. • Excellent communication skills, with the ability to explain complex AI concepts to non-technical stakeholders. Preferred Qualifications: • Experience with natural language processing (NLP), or reinforcement learning. • Experience with version control systems (e.g., Git) and CI/CD pipelines. • Familiarity with DevOps practices and tools for AI model deployment and monitoring. • Bachelors or Masters degree in Computer Science Engineering or Equivalent