Senior AI/ML Engineer

We are seeking a highly skilled and motivated Senior AI/ML Engineer to architect and build scalable, secure, fault-tolerant, and cost-effective AI systems with complex workflow orchestration and multi-agent decision-making capabilities. The ideal candidate will be responsible for architecting, developing, and deploying  AI systems by evaluating business needs and recommending optimal approaches like RAG, fine-tuned models, traditional ML, multi-agent frameworks, or hybrid solutions. The role requires a blend of hands-on machine learning expertise and software engineering proficiency to drive intelligent insights and business solutions.

• Design, develop, and scale complex multi-agent AI systems for high-performance, production-grade machine learning applications. 
• Architect scalable, fault-tolerant AI workflows within the Amazon Web Services ecosystem, leveraging Bedrock, SageMaker, Lambda, and EC2 with robust error handling, orchestration, and state management. 
• Rapidly prototype and validate AI solutions by designing experiments, evaluating performance metrics, and iteratively refining approaches to transform validated concepts into optimized, production-ready features. 
• Translate complex business requirements into technical AI/ML solutions 
• Collaborate cross-functionally with product, backend, and domain experts
• to align AI capabilities with business goals 
• Evaluate emerging AI technologies, present recommendations, and maintain comprehensive documentation of system architectures and operational runbooks 
• Work with LLMs, embedding models, and Retrieval-Augmented Generation (RAG) systems. 
• Ensure AI applications align with ethical standards, data privacy, and real-world scalability. 
• Develop, fine-tune, and optimize generative AI models
   

Requirements

• Work with current state-of-the-art LLMs and embedding models.
• Experience building agentic AI systems.
• Experience with debugging traces of LLM calls to identify errors/optimizations.
• Experience with building Retrieval-Augmented Generation (RAG) systems.
• Engineer and refine prompts to enhance AI performance and output quality.
• Knowledge of extracting structured outputs from LLMs.
• Experience using LLM APIs, embedding models, and RAG-based AI architectures.
• Strong skills in Python, AI model deployment, and AWS services (Lambda
  preferred).
• Knowledge of LangChain, Pydantic, and scalable AI workflows.
• Proficiency in prompt engineering and optimization techniques.
• Some UI/UX experience is a plus.
   

Preferred

• Experience in NLP, computer vision, or multimodal AI.
• Proven track record of deploying AI solutions at scale.
• Research background in generative AI models. 

Qualifications

• Minimum 5 years of experience in AI/ML development and data engineering.
• Proficiency in programming languages Python.
• Strong experience with machine learning frameworks (TensorFlow, PyTorch, Scikit-learn).
• Hands-on experience with data engineering tools like Apache Spark, Apache NiFi, Airflow, or similar.
• Expertise in handling large-scale datasets and implementing ETL/ELT pipelines.
• Experience with cloud platform (AWS) and containerization technologies (Docker, Kubernetes).
• Knowledge of database technologies (SQL, NoSQL, Data Lakes, Data Warehouses).
   

Preferred Qualifications

• Experience in NLP, Generative AI, or deep learning models.
• Knowledge of Big Data ecosystems such as Hadoop, Trino, or MinIO.
• Understanding of AI ethics, bias mitigation, and responsible AI principles.
• Prior experience in the financial or banking sector is a plus.