Senior Engineering Manager - AI & Data Engineering

About the Role

Key Responsibilities

• Develop AI-driven applications, microservices, and automation workflows using FastAPI, Flask, or Django, ensuring cloud-native deployment and performance optimization.
• Integrate OpenAI APIs (GPT models, Embeddings, Function Calling) and Retrieval-Augmented Generation (RAG) techniques to enhance AI-powered document retrieval, classification, and decision-making.
• Design, build, and optimize scalable data pipelines for AI/ML workflows using Pandas, PySpark, and Dask, integrating data sources such as Kafka, AWS S3, Azure Data Lake, and Snowflake.
• Enhance AI model inference efficiency by implementing vector retrieval using FAISS, Pinecone, or ChromaDB, and optimize API latency with tuning techniques (temperature, top-k sampling, max tokens settings).
• Develop scalable RESTful APIs for AI models and data services, ensuring integration with internal and external systems while securing API endpoints using OAuth, JWT, and API Key Authentication.
• Implement AI-powered logging, observability, and monitoring to track data pipelines, model drift, and inference accuracy, ensuring compliance with AI governance and security best practices.
• Work with AI/ML, Data Engineering, and DevOps teams to optimize AI model deployments, data pipelines, and real-time/batch processing for AI-driven solutions.
• Engage in Agile ceremonies, backlog refinement, and collaborative problem-solving to scale AI-powered workflows in areas like fraud detection, claims processing, and intelligent automation.
• Collaborate with Product, UX, and Compliance teams to align AI-powered features with user needs, security policies, and regulatory frameworks (HIPAA, GDPR, SOC2).
• Mentor junior engineers on AI model integration, API development, and scalable data engineering best practices, and conduct knowledge-sharing sessions.

Requirements

• 12-18 years of experience in software engineering or AI/ML development, preferably in AI-driven solutions.
• Hands-on experience with Agile development, SDLC, CI/CD pipelines, and AI model deployment lifecycles.
• Bachelor's Degree or equivalent in Computer Science, Engineering, Data Science, or a related field.
• Proficiency in full-stack development with expertise in Python (preferred for AI), Java.
• Experience with structured & unstructured data: SQL (PostgreSQL, MySQL, SQL Server), NoSQL (OpenSearch, Redis, Elasticsearch), Vector Databases (FAISS, Pinecone, ChromaDB).
• Cloud & AI Infrastructure experience: AWS (Lambda, SageMaker, ECS, S3), Azure (Azure OpenAI, ML Studio).
• Experience with GenAI frameworks & tools: OpenAI API, Hugging Face Transformers, LangChain, LlamaIndex, AutoGPT, CrewAI.
• Experience in LLM deployment, retrieval-augmented generation (RAG), and AI search optimization.
• Proficiency in AI model evaluation (BLEU, ROUGE, BERT Score, cosine similarity) and responsible AI deployment.
• Strong problem-solving skills, AI ethics awareness, and the ability to collaborate across AI, DevOps, and data engineering teams.
• Curiosity and eagerness to explore new AI models, tools, and best practices for scalable GenAI adoption.

Nice to Have

• Experience in retrieval-augmented generation (RAG), fine-tuning pre-trained LLMs, and AI model evaluation.
• Knowledge of AI governance, security, and compliance standards.

Qualifications

• Bachelor's Degree or equivalent in Computer Science, Engineering, Data Science, or a related field.

Benefits & Perks

• Health and financial benefits.
• Perks specific to each location, including commuter support, employee assistance programs, tuition assistance, employee resource groups, and collaborative workspaces.
• Flexible work arrangements to support work-life balance, including options for remote work.
• Sponsorship of events such as book clubs, external speakers, and hackathons.
• A company culture based on learning, support, inclusiveness, and valuing all employees.