
Cognilium AI helps organizations build scalable AI-powered products by combining cloud architecture, data pipelines, and automated operations. It provides AI-driven product engineering services across Cloud/MACH, DevOps automation, data engineering, machine learning, and generative AI. Advanced technologies include LangChain and retrieval-augmented generation, enabling scalable AI applications and high-quality data experiences. The company serves businesses across industries with augmenting team solutions and SaaS development, focusing on rapid delivery and client-centric learning. With 7+ years of experience and 50+ global clients, Cognilium AI aims to drive AI-driven insights and digital transformation.

Cognilium AI helps organizations build scalable AI-powered products by combining cloud architecture, data pipelines, and automated operations. It provides AI-driven product engineering services across Cloud/MACH, DevOps automation, data engineering, machine learning, and generative AI. Advanced technologies include LangChain and retrieval-augmented generation, enabling scalable AI applications and high-quality data experiences. The company serves businesses across industries with augmenting team solutions and SaaS development, focusing on rapid delivery and client-centric learning. With 7+ years of experience and 50+ global clients, Cognilium AI aims to drive AI-driven insights and digital transformation.
Cognilium AI is a production-first AI product engineering company building reliable, scalable AI systems for startups and enterprises. Founded in 2019, we specialize in agentic AI, enterprise-grade RAG/NL2SQL, voice AI, and cloud-native data platforms—engineered for real users, real scale, and measurable ROI.
We focus on shipping AI that works in production, not demos. With 100+ AI projects, 50+ production GenAI deployments, 99.9% uptime, and 300%+ average ROI, our work is defined by reliability, performance, and outcomes.
We operate as a remote-first, AWS-centric team with a builder-led culture. Our engineers own systems end-to-end—from architecture and implementation to deployment, observability, and optimization.
AI only matters when it works. That's what we build.
The Role:
We're hiring an AI & Backend Engineer to build and scale production-grade AI systems—not prototypes.
You'll design, implement, and operate LLM-powered backend services using Python and FastAPI, working on agentic workflows, RAG systems, and AI-driven APIs that are used in real production environments. This is a hands-on role with end-to-end ownership, from system design to deployment and optimization.
You'll work closely with product and engineering teams to turn business problems into reliable, scalable AI solutions, with a strong focus on performance, cost control, and operational stability.
If you enjoy shipping AI that actually runs in production—and taking ownership beyond just writing code—this role is built for you.
Key Responsibilities:
Build AI-Powered Systems:
Design, build, and deploy end-to-end generative AI applications
Implement LLM-powered workflows, including agentic and multi-step reasoning systems
Develop enterprise-grade RAG pipelines with grounding, citations, and guardrails
Backend & API Engineering:
Build high-performance, asynchronous APIs using Python and FastAPI
Design scalable microservices to expose AI capabilities
Implement authentication, rate limiting, background jobs, and service boundaries
LLM Integration & Prompt Engineering:
Integrate LLMs from OpenAI, Anthropic, and open-source providers
Design prompts that minimize hallucinations and control latency and cost
Work with vector databases to power retrieval and semantic search
System Architecture & Reliability:
Collaborate on system architecture with a production-first mindset
Design for scalability, fault tolerance, and security
Implement observability, structured logging, and monitoring across AI services
Deployment & MLOps:
Deploy AI services to cloud environments (AWS-first)
Containerize applications using Docker and support CI/CD pipelines
Apply MLOps best practices around evaluation, monitoring, rollback, and cost governance
Cross-Functional Collaboration:
Work closely with product managers, frontend engineers, and data teams
Translate business requirements into robust technical implementations
Participate in architecture reviews and technical decision-making
Required Qualifications:
Strong backend engineering experience with Python
Hands-on experience building APIs using FastAPI
Practical experience developing applications using Large Language Models (LLMs)
Proven experience building generative AI or RAG-based systems
Solid understanding of RESTful API design, service architecture, and best practices
Preferred Qualifications (Bonus Points):
Experience deploying systems on AWS, GCP, or Azure
Familiarity with LangChain, LlamaIndex, LangGraph, or CrewAI
Experience with Docker, Kubernetes, and CI/CD pipelines
Familiarity with vector databases (Pinecone, Weaviate, Qdrant, Chroma, OpenSearch)
Experience with SQL and/or NoSQL databases
Exposure to voice AI or real-time systems
What We Offer:
Competitive salary and equity package
Comprehensive health, dental, and vision insurance
Flexible time off and remote work options
The opportunity to work on challenging problems at the intersection of AI and technology
A collaborative and innovative work environment
How to Apply:
Please send your resume to: jawaria@cognilium.ai
Or fill the application form: https://forms.gle/aeG8UFEv9Qo1Dgg76