Role Overview
We are looking for a highly skilled AI Manager with 7-10 years of experience to design, develop, and deploy enterprise-scale AI/ML and Generative AI solutions for consulting clients across Financial Services and other industries. The ideal candidate will combine strong backend engineering expertise in Python with deep knowledge of AI/ML frameworks, large language models, and cloud-native architectures, and will collaborate closely with data science, frontend, DevOps, and client-facing consulting teams.
Key Responsibilities
- Design, develop, and maintain scalable backend services and RESTful APIs using Python (Django, Flask, or FastAPI) to power AI/ML and GenAI workloads
- Architect and build LLM-powered applications using RAG, prompt engineering, fine-tuning, and agentic AI frameworks (LangChain, LlamaIndex, CrewAI)
- Develop and maintain production ML pipelines including data ingestion, feature engineering, model training, evaluation, and deployment
- Implement MLOps/AIOps best practices including model versioning, monitoring, governance, and CI/CD for ML systems
- Work with databases (SQL - PostgreSQL/MySQL and NoSQL - MongoDB, Redis) and vector databases (Pinecone, Weaviate, FAISS) to ensure performance and reliability
- Deploy and manage services using Docker, Kubernetes, and CI/CD pipelines on cloud platforms (AWS / Azure / GCP) leveraging cloud-native AI services (SageMaker, Bedrock, Vertex AI, Azure AI)
- Design microservices architecture and event-driven systems to support scalable, distributed AI solutions
- Implement secure, high-performance backend components with best practices for authentication, authorization, data security, and AI governance
- Collaborate with consulting and client-facing teams to translate business requirements into technical solutions and present recommendations to stakeholders
- Participate in architecture discussions, pre-sales, client pursuits, and proposal development
- Ensure best practices for code quality, testing, and documentation across backend and AI/ML codebases
- Mentor junior developers and AI engineers and contribute to team growth
Required Skills & Qualifications
- 5-8 years of hands-on experience in Python backend development and AI/ML engineering
- Master's degree in Computer Science, Engineering, Data Science, AI, or a related STEM field
- Strong experience with frameworks such as Django, Flask, or FastAPI
- Expertise in API development (REST, GraphQL) and backend architecture
- Experience with SQL (PostgreSQL/MySQL) and NoSQL (MongoDB, Redis, etc.)
- Strong understanding of microservices architecture and event-driven systems (Kafka, RabbitMQ)
- Deep proficiency in TensorFlow, PyTorch, scikit-learn, and ML libraries/frameworks
- Hands-on experience with LLMs, NLP, RAG architectures, prompt engineering, and fine-tuning
- Experience with cloud platforms (AWS / Azure / GCP) and cloud-native AI services (SageMaker, Bedrock, Vertex AI, Azure AI)
- Strong understanding of MLOps - model versioning, monitoring, cost optimization, and governance
- Experience with vector databases (Pinecone, Weaviate, Milvus, FAISS) and embedding models
- Proficiency in Docker, Kubernetes, and CI/CD pipelines
- Solid understanding of authentication, authorization, data security, and AI governance best practices
- Excellent communication skills with the ability to articulate complex technical concepts to non-technical stakeholders
- Experience working in agile and consulting environments
Good to Have
- Experience building multi-agent systems (task delegation, coordination, and autonomous decision-making)
- Experience with computer vision, deep learning, or reinforcement learning
- Familiarity with big data technologies (Spark, Databricks, Snowflake)
- Knowledge of responsible AI, AI safety, and model explainability
- Prior experience working with global financial services clients
What We Offer
- Opportunity to work on cutting-edge AI, GenAI, and Agentic AI products for top-tier consulting clients
- Collaborative and fast-growing work environment
- Competitive compensation
- High ownership and impact-driven role
- Learning and growth opportunities in advanced AI technologies and consulting delivery
- Exposure to global clients across Financial Services and enterprise domains
