AI Engineer

AI Engineer
Experience: 2+ Years
About the Role
We are looking for an AI Engineer with strong AI/ML fundamentals, software engineering skills, and hands-on experience building and deploying production-grade AI systems.
The role involves working across the AI engineering lifecycle — from model and LLM integration to backend development, system design, deployment, and production operations. Strong programming skills in Python and Go, along with practical experience in modern AI technologies and scalable systems, are essential.
Key Responsibilities
AI & GenAI Engineering
Design and build production-grade AI/ML and LLM-powered applications.
Develop RAG systems using embeddings, semantic search, vector databases, retrieval, and reranking.
Build tool-calling, workflow-based, and agentic AI systems where appropriate.
Work with ML/DL models, LLMs, and multimodal models based on application requirements.
Implement evaluation, validation, guardrails, and fallback mechanisms for AI applications.
Optimize AI systems for quality, latency, reliability, scalability, and cost.
Software Engineering & System Design
Build maintainable production services using Python and Go (Golang).
Design and develop REST/gRPC APIs and reusable backend components.
Design scalable and reliable architectures for AI applications.
Apply system design and distributed-system principles to make appropriate architectural decisions.
Work with databases, caching, messaging, and supporting backend infrastructure.
Follow strong engineering practices around testing, code reviews, version control, and documentation.
Production Deployment & Infrastructure
Deploy and operate AI applications in production using Docker and cloud platforms such as AWS, Azure, or GCP.
Build and maintain CI/CD pipelines and production deployment workflows.
Work with Kubernetes or equivalent orchestration technologies.
Implement logging, monitoring, tracing, configuration, secrets management, and reliable rollback strategies.
Troubleshoot production issues across AI, application, and infrastructure layers.
Continuously improve system performance, reliability, and infrastructure efficiency.
Required Skills
2+ years of relevant AI/ML or Software Engineering experience.
Strong programming skills in Python and working experience with Go (Golang).
Strong software engineering fundamentals, including Data Structures, Algorithms, APIs, databases, Git, and testing.
Solid understanding of Machine Learning and Deep Learning fundamentals, with experience using PyTorch, TensorFlow, or equivalent.
Hands-on experience with LLMs, RAG, embeddings, semantic search, and vector databases.
Good understanding of system design and distributed-system fundamentals.
Hands-on experience with Docker, cloud infrastructure, CI/CD, and production deployment.
Experience building, deploying, and maintaining production-grade AI/ML applications.
Strong problem-solving, debugging, and engineering judgment.
Education
Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, Computer Engineering, Information Technology, or a related technical discipline.
Good to Have
Experience with Kubernetes, Terraform, MLflow, Kafka, Redis, PostgreSQL, or similar production technologies.
Experience with LLM orchestration and agentic frameworks such as LangGraph or equivalent.
Exposure to model serving, inference optimization, GPU workloads, and high-throughput AI systems.
What We Look For
Engineering mindset: Ability to build reliable, maintainable, production-quality AI systems.
Ownership: Ability to take problems from requirements and design through implementation and deployment.

Work arrangement
No