SPECIFIC DUTIES AND RESPONSIBILITIES

• Design, build, and deploy AI/ML solutions using GCP Vertex AI, BigQuery ML, and AI Platform for model training, deployment, and serving
• Develop and maintain platform services for AI agent orchestration, RAG pipelines, and LLM integration using Python, FastAPI, and Flask
• Collaborate with cross-functional teams to support CI/CD pipelines for ML models, GitLab workflows, and MLOps automation
• Work with GCP services including Cloud Functions, Cloud Run, Dataflow, and Pub/Sub to build event-driven AI architectures
• Build and optimize data pipelines using BigQuery, Dataflow, and Apache Airflow for AI model training and inference
• Contribute to automation, observability, and reliability initiatives for AI systemsusing GCP Cloud Operations and New Relic
• Lead and mentor team members in AI/ML engineering best practices, fostering a culture of learning and innovation
• Explore and integrate cutting-edge AI capabilities (LLMs, vector databases, prompt engineering) into platform solutions
• Develop customized AI solutions and integrations to meet development teams' requirements, leveraging GCP APIs, SDKs, and LangChain
• Create technical documentation, tutorials, and training materials to support AI/ML adoption and facilitate knowledge transfer
• Stay up to date on latest AI/ML technologies, GCP products, and industry trends, serving as a subject matter expert for the organization
• Analyze existing AI workflows and processes to identify areas for optimization and efficiency gains
• Implement scalable AI systems and tools to automate repetitive tasks, streamline ML operations, and enhance developer productivity

COMPETENCIES

Core Competencies (Must-have Competencies)

• 7+ years of experience in Software Engineering
• 3+ years of experience focusing on AI/ML engineering, specializing in scalable AI infrastructure and model deployment
• 3+ years of experience in Python for AI/ML development (TensorFlow, PyTorch)
• 2+ years of experience with GCP AI/ML services (Vertex AI, BigQuery ML, AI Platform, AutoML)
• 1+ years of experience building and deploying production AI systems including LLM integration, RAG architectures, and vector databases
• 5+ years of experience with Git, Docker, and Kubernetes for containerized ML workloads
• 1+ years of experience in problem-solving skills and a proactive attitude toward learning new AI technologies

Complementary Competencies (Good-to-have Competencies)

• Experience with LangChain or other LLM orchestration frameworks
• Knowledge of vector databases and semantic search
• Experience with agentic AI frameworks, React patterns, or autonomous agent architectures
• Familiarity with prompt engineering, fine-tuning, and LLM evaluation techniques
• Knowledge of service mesh, API gateways, or event-driven architecture on GCP
• Contributions to open-source AI/ML projects or technical communities
• Experience with Cohere, Anthropic Claude, or Google Gemini
• Knowledge of testing frameworks for ML systems (unit tests, model validation, A/B
• testing)

QUALIFICATIONS

Educational Qualification/s

• University degree in computer science, software engineering, or other relevant discipline, or equivalent combination of education and experience.