Generative AI Engineer

AI Engineer / Generative AI Engineer (4–6 Years Experience)

Job Summary

We are seeking a talented and motivated AI Engineer / Generative AI Engineer with 4–6 years of experience to design, develop, and deploy AI-driven solutions that deliver business value across the organization. This role focuses on building and integrating Generative AI applications, supporting Responsible AI practices, and embedding AI capabilities throughout the Software Development Life Cycle (SDLC).

The ideal candidate will have hands-on experience with Large Language Models (LLMs) such as OpenAI (ChatGPT) and Anthropic (Claude), along with exposure to agentic AI systems, AI automation frameworks, and modern AI engineering practices.

Key Responsibilities

AI Development & Implementation

• Design, develop, and deploy AI/ML and Generative AI solutions to address business challenges.
• Build applications leveraging Large Language Models (LLMs) such as OpenAI and Anthropic models.
• Implement prompt engineering strategies and model evaluation frameworks.
• Support model fine-tuning, optimization, and performance enhancement where applicable.
• Collaborate with cross-functional teams to identify and prioritize AI use cases.

LLM & Generative AI Solutions

• Develop and integrate LLM-powered applications, including chatbots, copilots, virtual assistants, and automation tools.
• Create reusable prompt libraries, workflows, and AI solution patterns.
• Evaluate model outputs for accuracy, reliability, safety, and business effectiveness.
• Implement Retrieval-Augmented Generation (RAG) and knowledge-based AI solutions where required.

AI Integration into SDLC

• Embed AI capabilities into existing enterprise applications and business workflows.
• Contribute to AI-assisted software development, testing, automation, and quality engineering initiatives.
• Collaborate with DevOps teams to establish CI/CD pipelines for AI-enabled applications.
• Support deployment, monitoring, and lifecycle management of AI services.

Agentic AI & Automation

• Assist in building agent-based workflows and intelligent automation solutions.
• Work with orchestration frameworks and tools to enable multi-step reasoning and task execution.
• Support the development of context-aware, goal-driven, and autonomous AI agents.
• Integrate external tools, APIs, and enterprise systems into agentic workflows.

AI Governance, Security & Compliance

• Adhere to Responsible AI principles, governance frameworks, and organizational standards.
• Ensure AI solutions comply with data privacy, security, and regulatory requirements.
• Support implementation of monitoring, logging, auditability, and risk-control mechanisms.
• Participate in AI model evaluation and governance reviews.

Collaboration & Delivery

• Partner with product managers, software engineers, architects, and data teams to deliver AI solutions.
• Translate business requirements into scalable and practical AI implementations.
• Contribute to technical documentation, architecture artifacts, and knowledge-sharing initiatives.
• Stay current with emerging AI technologies, frameworks, and industry best practices.

Required Technical Skills

AI, ML & Generative AI

• Hands-on experience developing Generative AI and LLM-based applications.
• Experience with OpenAI (ChatGPT), Anthropic (Claude), or similar AI platforms.
• Strong understanding of prompt engineering, prompt optimization, and model evaluation techniques.
• Knowledge of Retrieval-Augmented Generation (RAG), embeddings, and vector search concepts.
• Familiarity with AI model performance measurement and validation.

Programming & Software Development

• Strong proficiency in Python (preferred) or other modern programming languages.
• Experience building RESTful APIs, microservices, and backend services.
• Familiarity with AI/ML frameworks and libraries such as LangChain, LlamaIndex, Hugging Face, PyTorch, or TensorFlow.
• Understanding of software engineering best practices, including testing, version control, and code quality.

Architecture & Integration

• Understanding of scalable system design and distributed application architecture.
• Experience integrating third-party APIs, AI services, and enterprise applications.
• Exposure to cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).
• Familiarity with containerization technologies such as Docker and Kubernetes is desirable.

DevOps & MLOps

• Experience with CI/CD pipelines and DevOps practices.
• Basic understanding of MLOps concepts, including model deployment, monitoring, versioning, and lifecycle management.
• Familiarity with observability and monitoring tools for AI systems.

Data Security & Compliance

• Understanding of data privacy, security, and governance principles.
• Awareness of compliance frameworks and standards such as GDPR, SOC 2, ISO 27001, and related regulations.
• Knowledge of secure AI development practices and responsible AI principles.

Preferred Qualifications

• Experience delivering Generative AI, conversational AI, or chatbot solutions in production environments.
• Exposure to agent frameworks and workflow orchestration tools.
• Experience with vector databases such as Pinecone, Weaviate, Chroma, or similar technologies.
• Familiarity with AI observability, monitoring, and evaluation platforms.
• Knowledge of RAG architectures, semantic search, and enterprise knowledge management solutions.
• Experience working in Agile development environments.

Soft Skills

• Strong analytical and problem-solving abilities.
• Excellent communication and stakeholder management skills.
• Ability to work effectively in cross-functional teams.
• Strong learning agility and adaptability in a rapidly evolving AI landscape.
• Balanced approach to hands-on development, architecture thinking, and business problem-solving.

Education

• Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
• Relevant certifications in AI, Machine Learning, Cloud Platforms, or Generative AI technologies are an added advantage.