Senior Backend Engineer

Company: Grey Chain AI

Location: Remote

Experience: 7+ Years

Employment Type: Full Time

About the Role

We are looking for a Senior Python AI Engineer who will lead the design, development, and delivery of production-grade GenAI and agentic AI solutions for global clients. This role requires a strong Python engineering background, experience working with foreign enterprise clients, and the ability to own delivery, guide teams, and build scalable AI systems.

You will work closely with product, engineering, and client stakeholders to deliver high-impact AI-driven platforms, intelligent agents, and LLM-powered systems.

Key Responsibilities

• Lead the design and development of Python-based AI systems, APIs, and microservices.
• Architect and build GenAI and agentic AI workflows using modern LLM frameworks.
• Own end-to-end delivery of AI projects for international clients, from requirement gathering to production deployment.
• Design and implement LLM pipelines, prompt workflows, and agent orchestration systems.
• Ensure reliability, scalability, and security of AI solutions in production.
• Mentor junior engineers and provide technical leadership to the team.
• Work closely with clients to understand business needs and translate them into robust AI solutions.
• Drive adoption of latest GenAI trends, tools, and best practices across projects.
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Must-Have Technical Skills

• 7+ years of hands-on experience in Python development, building scalable backend systems.
• Strong experience with Python frameworks and libraries (FastAPI, Flask, Pydantic, SQLAlchemy, etc.).
• Solid experience working with LLMs and GenAI systems (OpenAI, Claude, Gemini, open-source models).
• Good experience with agentic AI frameworks such as LangChain, LangGraph, LlamaIndex, or similar.
• Experience designing multi-agent workflows, tool calling, and prompt pipelines.
• Strong understanding of REST APIs, microservices, and cloud-native architectures.
• Experience deploying AI solutions on AWS, Azure, or GCP.
• Knowledge of MLOps / LLMOps, model monitoring, evaluation, and logging.
• Proficiency with Git, CI/CD, and production deployment pipelines.

Leadership & Client-Facing Experience

• Proven experience leading engineering teams or acting as a technical lead.
• Strong experience working directly with foreign or enterprise clients.
• Ability to gather requirements, propose solutions, and own delivery outcomes.
• Comfortable presenting technical concepts to non-technical stakeholders.

What We Look For

• Excellent communication, comprehension, and presentation skills.
• High level of ownership, accountability, and reliability.
• Self-driven professional who can operate independently in a remote setup.
• Strong problem-solving mindset and attention to detail.
• Passion for GenAI, agentic systems, and emerging AI trends.

Why Grey Chain AI

Grey Chain AI is a Generative AI-as-a-Service and Digital Transformation company trusted by global brands such as UNICEF, BOSE, KFINTECH, WHO, and Fortune 500 companies. We build real-world, production-ready AI systems that drive business impact across industries like BFSI, Non-profits, Retail, and Consulting.

Here, you won’t just experiment with AI — you will build, deploy, and scale it for the real world.

The candidate should have extensive experience in designing and developing scalable data pipelines and real-time data processing solutions. As a key member of the team, the Senior Data Engineer will play a critical role in building end-to-end data workflows, supporting machine learning model deployment, and driving MLOps practices in a fast-paced, agile environment. Strong expertise in Apache Kafka, Apache Flink, AWS SageMaker, and Terraform is essential. Additional experience with infrastructure automation and CI/CD for ML models is a significant advantage.

Key Responsibilities

1. Design, develop, and maintain high-performance ETL and real-time data pipelines using Apache Kafka and Apache Flink.
2. Build scalable and automated MLOps pipelines for training, validation, and deployment of models using AWS SageMaker and associated services.
3. Implement and manage Infrastructure as Code (IaC) using Terraform to provision and manage AWS environments.
4. Collaborate with data scientists, ML engineers, and DevOps teams to streamline model deployment workflows and ensure reliable production delivery.
5. Optimize data storage and retrieval strategies for large-scale structured and unstructured datasets.
6. Develop data transformation logic and integrate data from various internal and external sources into data lakes and warehouses.
7. Monitor, troubleshoot, and enhance performance of data systems in a cloud-native, fast-evolving production setup.
8. Ensure adherence to data governance, privacy, and security standards across all data handling activities.
9. Document data engineering solutions and workflows to facilitate cross-functional understanding and ongoing maintenance.

• Java
• Springboot
• REST API
• Microservices

• 3-5 Years of experience in Backend Development.
• Must have experience in Python (FLASK framework).
• Have Deep understanding of how RESTful APIs work.
• Familiar with various design and architectural patterns that can work at scale.
• Sound knowledge of NoSQL/SQL Databases (Mongo DB preferred).
• Strong experience with at-Cloud technology, preferably AWS or GCP or Azure.
• Core experience in developing complex backend systems.
• Communicating complex technical concepts to both technical and non-technical audiences.
• Passionate about application scalability, availability, reliability, and security.