Senior AI Engineer

Job Description

Location: Manbhawan, Lalitpur (On-site / Hybrid)

Department: AI

Reports To: Chief Technology Officer (CTO)

To apply, please send your resume to [email protected].

We are seeking a highly skilled Senior AI Engineer to design, develop, and deploy production-grade AI/ML solutions that drive tangible business value. In 2026, building AI systems goes beyond API integration; you will lead the architecture of advanced multi-agent workflows, state-of-the-art retrieval systems (RAG), and custom-tuned open-source models. This role requires deep technical expertise, robust engineering discipline, and a proven track record of shipping scalable, secure, and cost-optimized AI applications to production.

• Design and implement complex multi-agent orchestration workflows, autonomous AI agents, and advanced graph-based RAG architectures.
• Lead fine-tuning strategies for open-source Large and Small Language Models (LLMs/SLMs) using techniques like LoRA/QLoRA to meet domain-specific needs.

• Establish rigorous validation pipelines and evaluation frameworks to systematically measure and mitigate hallucinations, latency, and token spend.
• Implement production-grade guardrails to monitor and secure AI systems against prompt injection, data leakage, and adversarial vulnerabilities.

• Convert trained models into high-throughput microservices, integrating them seamlessly into live production software.
• Build and maintain scalable backend workflows and APIs (FastAPI/Flask) optimized for low-latency model inference.

• Architect and manage the full ML lifecycle, including model versioning, continuous deployment, automated retraining, and data drift detection.
• Build robust data handling pipelines for cleaning, synthetic data generation, and context-enrichment of large-scale datasets.

• Optimize inference costs and token consumption through efficient context-window management, model quantization, and caching strategies.

• Guide and mentor junior AI engineers, establish coding standards, and conduct architecture and code reviews.
• Partner with product and engineering teams to translate high-level business goals into concrete AI-driven technical specifications.

• Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a closely related field.
• Experience: 5+ years of experience in production-level Machine Learning or AI Engineering roles.
• Core ML Stack: Strong proficiency in Python and deep learning frameworks, specifically PyTorch and the Hugging Face ecosystem.
• GenAI Stack: Hands-on experience building with orchestration frameworks (e.g., LangGraph, AutoGen, LlamaIndex, LangChain).
• Vector Infrastructure: Experience setting up, indexing, and optimizing vector databases (e.g., Pinecone, Qdrant, Milvus, or pgvector).
• Cloud & Infrastructure: Strong experience deploying and managing AI workloads on cloud platforms (AWS, GCP, or Azure) utilizing Docker and Kubernetes.
• LLMOps Tools: Familiarity with LLM tracking, evaluation, and observability tools (e.g., LangSmith, Phoenix, Ragas, or MLflow).

• Experience deploying local, open-source models using high-performance inference engines like vLLM, Ollama, or TensorRT-LLM.
• Familiarity with distributed data processing and big data frameworks (e.g., Spark, Databricks).
• Active contributor to open-source AI projects or author of peer-reviewed AI research publications.
• Exceptional communication skills with the ability to articulate complex AI paradigms to non-technical stakeholders.

• Cutting-Edge Tech Stack: Opportunity to build pioneering GenAI, Agentic, and LLM applications utilizing industry-leading infrastructure.
• Premium Compute Access: Dedicated and flexible cloud compute budgets and access to high-end cluster GPUs for model training and inference experimentation.
• Collaborative Environment: A culture of innovation, continuous learning, and intellectual curiosity at our tech hub in Manbhawan.
• Growth & Leadership: Clear pathways to AI leadership and architectural ownership as the AI department expands.
• Compensation: Highly competitive salary package, performance bonuses, and a comprehensive benefits structure.