Senior AI Engineer WFH
- Kolkata, India
نُشرت قبل 7 أيام
عن الوظيفة
Read everything carefully. The requirements and screening questions are critical and if not answered correctly will result in rejection.
- Work from Home.
- This is a full-time role. If you plan to do 2 or more jobs at the same time or want to do this part-time, that won't work for us. In that case please do not apply as it will get auto-rejected
- Note - this job requires working late night India time until 4AM to overlap with USA working times. Do not apply if this timing doesn't work
- Salary depends on experience and current verifiable (paychecks) compensation.
- Senior candidates with more than 3 years experience are suitable
We are searching for a startup guru who has hands on experience in working on AI agents and frameworks, open source AI models etc. Someone who has previous experience with owning the whole product and roadmap from AI and back-end standpoint. Must be a coder, not just data science background. Someone who is not shy in going overboard to launch a world-class product.
Salary depends on experience and current verifiable (paychecks) compensation.
Company Description
Headquartered in McLean, Virginia, USA, Qubrid is a global provider of Artificial Intelligence (AI), Data Center and IoT products, solutions, and services. As pioneers in the realm of advanced computing technologies, we pride ourselves on being at the forefront of innovation, empowering businesses with the transformative capabilities of GPUs, Artificial Intelligence, Quantum Computing, IoT and more. We specialize in offering a wide array of hardware and software solutions for industries such as healthcare, manufacturing, finance, government, education and more.
Position - Senior AI Engineer
Preferred location - Kolkata, India or Delhi, India
About the Role
We’re looking for a Senior AI Engineer to design and build end-to-end AI systems—from model deployment and optimization to autonomous agent orchestration.
This is not a research-only role. You’ll operate at the intersection of:
• LLMs & multimodal models
• agent frameworks and workflow orchestration
• production-grade infrastructure
You will help define how intelligent systems are built, deployed, and scaled in real-world environments.
What You’ll Work On
• Design and implement autonomous AI agents capable of multi-step reasoning, tool use, and workflow execution
• Build agent orchestration systems (memory, planning, tool calling, state management)
• Deploy and serve models (LLMs, vision, multimodal) in production environments
• Optimize models via:
◦ fine-tuning (LoRA, full fine-tune)
◦ quantization (INT8, 4-bit, GGUF, etc.)
◦ distillation and performance tuning
• Develop multi-model pipelines (generation + retrieval + tools + agents)
• Integrate external tools/APIs into agent workflows
• Build evaluation systems for:
◦ reasoning quality
◦ hallucination detection
◦ task success rates
Core Responsibilities
AI / ML Systems
• Architect and implement end-to-end AI pipelines
• Work with open-source and proprietary models (LLMs, diffusion, etc.)
• Implement RAG systems, embeddings, and vector search
• Design prompting + system instruction strategies
• Improve latency, throughput, and cost efficiency
Infrastructure & Deployment
• Deploy models using modern stacks (containers, GPUs, serverless where applicable)
• Build scalable inference systems
• Manage model versioning, monitoring, and rollback strategies
• Work with distributed systems and async processing pipelines
Agent & Workflow Engineering
• Build custom agent frameworks or extend existing ones
• Implement:
◦ planning / reasoning loops
◦ tool usage
◦ memory (short-term + long-term)
• Design reusable workflows for real-world use cases
Software Engineering Excellence
• Write clean, maintainable, production-grade code (Python primarily)
• Design APIs and services for internal and external use
• Collaborate with product and design to ship user-facing features
Process & Engineering Rigor
• Write clear technical requirements (PRDs / tech specs)
• Produce and maintain technical documentation
• Conduct code reviews and enforce engineering standards
• Define evaluation metrics and testing strategies for AI systems
• Participate in architecture discussions and system design
Requirements
Must-Have
• 3-5+ years in software engineering, with strong focus on AI/ML systems
• Hands-on experience with LLMs and/or multimodal models
• Experience building or working with AI agents or multi-step workflows
• Strong Python skills and familiarity with ML frameworks (PyTorch, etc.)
• Experience with:
◦ model deployment (Docker, cloud, GPU infra)
◦ fine-tuning and/or quantization
• Solid understanding of:
◦ prompt engineering
◦ RAG architectures
◦ embeddings + vector databases
Nice-to-Have
• Experience with frameworks like LangChain, LlamaIndex, or custom agent systems
• Familiarity with model serving tools (vLLM, TensorRT, ONNX, etc.)
• Experience with distributed systems and high-scale APIs
• Background in performance optimization / systems engineering
• Contributions to open-source AI projects
What We Value
• Builders who ship, not just experiment
• Strong systems thinking (not just model-level thinking)
• Ability to move between research ideas → production systems
• Clear communication and documentation habits
• Ownership mindset and product intuition
Why This Role
• Work on cutting-edge agent systems, not just wrappers
• High ownership and ability to shape architecture
• Build a full-stack AI platform, not a narrow feature
• Fast-moving environment with real-world impact