GenAI Developer

Key Responsibilities

• AI Architect Designs and oversees the AI strategy, ensuring solutions are

scalable, adaptable, and aligned with business objectives. They establish AI

frameworks, integrate systems, and provide guidance on infrastructure.

• AI Engineering Develops and deploys AI models, optimizing performance and

ensuring seamless integration into existing workflows. They fine-tune algorithms,

uses methods like RAG, Vector Databases and focus on real-world

implementation. Develops and executes test plans to validate AI models,

identifying performance issues and potential biases.

• Design and Development: Develop AI models and algorithms tailored to the

specific needs of the business. Experience with Natural Language Processing

(NLP), prompt engineering, etc. Works with existing data science team where

applicable.

• AI Testing & Validation Responsibilities include:
• Ensure AI solutions perform reliably and ethically.
• Quality Assurance Conducts functional and non-functional testing,

ensuring AI applications meet performance, security, and scalability

requirements.

• Data Validation Monitors training data quality, ensuring accuracy,

integrity, and consistency while minimizing errors and biases.

• Model Evaluation Assesses AI models through rigorous validation

techniques, including cross-validation and error analysis, to refine

performance.

• AI Ethics Auditing– Reviews AI decisions for fairness, transparency, and

compliance with regulations, adjusting models where necessary.

• Deployment: Experience deploying models into production environments and

working with teams to integrate solutions into existing software applications and

platforms. Familiarity with CI/CD pipelines.

• Data Analysis: Analyze large datasets to extract meaningful insights and

patterns; including interoperable data that may not be fully first party data.

Strong understanding of supervised/unsupervised learning, neural networks,

model evaluation and handling data at scale.

• Optimization: Have a passion for continual learning, optimizing AI models for

performance and accuracy.

• Research: Stay updated with the latest AI advancements and integrate

cutting-edge technologies into projects.

• Collaboration: Work closely with cross-functional teams to understand business

requirements and deliver effective solutions.

• Documentation: Prepare comprehensive documentation for developed AI models

and algorithms.

• Testing: Conduct rigorous testing and validation to ensure robustness and

reliability of AI solutions.

Qualifications:

• Education: Bachelor's or Master's degree in Computer Science, Engineering,

Mathematics, or in related field.

• Experience: 5 to 8+ years of professional experience in software engineering,

machine learning, or AI. 3+ years specifically working with generative AI

models (e.g., transformers, diffusion models, LLMs like GPT, image generation

models like Stable Diffusion or DALL•E).

• Technical Skills: Proficiency in programming languages such as Python, Java,

C++, and frameworks like TensorFlow, PyTorch or Tensorflow and ML

frameworks.

• Proficient in LLM Frameworks such as LangChain, LlamaIndex, OpenAI API.
• Analytical Skills: Strong analytical and problem-solving skills.
• Communication: Excellent verbal and written communication skills.
• Team Player: Ability to work collaboratively in a team environment and mentor

junior developers.

• Creativity: Ability to think creatively and develop innovative solutions.

Preferred Skills and Experience

• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Knowledge of big data technologies and databases.
• Familiarity with natural language processing (NLP) and computer vision.
• Understanding of software development lifecycle and agile methodologies.
• Experience with version control systems like Git.