The Opportunity
AI Engineer (overall, 6-10 years with at least 2 years of AI Dev experience)
Design, develop and deploy enterprise-grade AI solutions, including AI Agents, RAG-based applications, Intelligent Automation workflows and LLM-powered platforms. The candidate will work closely with Architects, Product Owners, Data Engineers, and Business Stakeholders to build scalable, secure, and production-ready AI systems that integrate with enterprise applications and data platforms. This role requires both strong software engineering capabilities and practical expertise in Generative AI technologies.AI Agent Development
· Design and implement autonomous and semi-autonomous AI Agents
· Implement tool calling and function calling capabilities
· Create prompt templates and prompt optimization strategies
· Define agent workflows and state management
· Optimize retrieval accuracy and response quality
· Implement knowledge grounding mechanisms
· Integrate AI solutions with enterprise systems through APIs
· Consume and expose REST APIs
· Work with structured and unstructured data sources
· Build data pipelines for AI applications
· Deploy AI solutions in cloud environments
· Implement CI/CD pipelines for AI applications
Programming Languages
· Python (Mandatory)
· JavaScript / TypeScript
AI Frameworks - Experience with one or more:
- LangChain
- LangGraph
Backend Development
- REST APIs
- GraphQL
- FastAPI
Cloud Platforms - Experience with AWS
- Lambda
- S3
- ECS/EKS
What you'll do
- Design and develop AI Agents, RAG applications, and intelligent automation solutions.
- Build and optimize agent workflows, prompt strategies, and knowledge retrieval mechanisms.
- Develop backend services and APIs using Python, FastAPI, REST APIs, and GraphQL.
- Integrate AI solutions with enterprise applications, data platforms, and external systems.
- Build and deploy cloud-native AI applications on AWS (Lambda, S3, ECS/EKS).
- Implement CI/CD pipelines and follow software engineering best practices for scalable deployments.
What you'll bring
- 6-10 years of software engineering experience, including at least 2 years of hands-on AI/Generative AI development experience.
- Strong programming expertise in Python (mandatory) and working knowledge of JavaScript/TypeScript.
- Experience building AI Agents, RAG-based solutions, LLM-powered applications, and other Generative AI solutions.
- Hands-on experience with LangChain, LangGraph, or similar AI orchestration frameworks.
- Strong understanding of RAG architectures, vector databases, embeddings, prompt engineering, and knowledge grounding techniques.
- Experience developing and integrating REST APIs, GraphQL services, and FastAPI-based applications.
- Cloud deployment experience on AWS, including Lambda, S3, ECS, and EKS.
- Familiarity with enterprise integrations, API development, data pipelines, and working with structured and unstructured data sources.
- Knowledge of CI/CD pipelines, containerization, and cloud-native architectures.
- Ability to collaborate effectively with architects, data engineers, product owners, and business stakeholders.
- Strong analytical, problem-solving, and communication skills with a focus on delivering scalable, secure, and production-ready AI solutions.
AI Fluency Expected
Good to Have
- Experience with Vector Databases such as Pinecone, Weaviate, Chroma, or FAISS.
- Exposure to MLOps/LLMOps practices, including model monitoring, evaluation, and AI observability.
- Experience with Docker, Kubernetes, and containerized AI application deployments.
- Familiarity with Azure OpenAI, Amazon Bedrock, OpenAI APIs, or similar enterprise AI platforms.
- Experience building multi-agent systems, intelligent automation workflows, and agent orchestration frameworks.
- Working knowledge of machine learning concepts, embeddings, fine-tuning, and model evaluation techniques.
- Experience with streaming data pipelines, event-driven architectures, and distributed systems.
- Understanding of security, governance, responsible AI, and enterprise compliance requirements.
- Exposure to DevOps best practices, Infrastructure as Code (Terraform/CloudFormation), and automated deployment pipelines.
- Certification in AWS, Generative AI, or cloud-native technologies is a plus.
Ready to make an impact?
Submit your application today and join the Myridius team.