We are looking for an experienced AI Engineer who can independently understand business problems, select the right technical approach and build reliable AI solutions from experimentation through production.

This is a hands-on role requiring strong engineering fundamentals, systematic problem-solving and ownership of solution quality, performance and scalability. You will work closely with Product, Delivery, Engineering, QA and client-facing teams.

Key Responsibilities

- Own end-to-end AI development: Take solutions through research, Proof of Concept, development, testing, UAT, production deployment and ongoing improvement.
- Build ML and Deep Learning solutions: Develop pipelines covering data preparation, feature engineering, model selection, training, optimization, validation, monitoring and retraining.
- Develop Generative AI applications: Build RAG, knowledge retrieval and agentic solutions using prompt engineering, embeddings, vector databases, structured outputs and tool calling.
- Select and optimize models: Evaluate open-source and commercial LLMs, SLMs and classical ML models based on accuracy, latency, privacy, cost and business requirements. Apply fine-tuning and optimization techniques where appropriate.
- Validate AI quality: Create benchmark datasets, automated evaluations and regression tests to assess accuracy, relevance, groundedness, completeness, consistency and hallucination.
- Engineer for production: Address concurrency, batching, caching, asynchronous processing, GPU utilization, throughput, failure handling and infrastructure cost.
- Implement MLOps and LLMOps: Establish versioning, experiment tracking, CI/CD, controlled deployments, observability, drift detection and rollback practices.
- Build application services: Develop robust Python backend services, APIs and integrations, with sufficient frontend capability to independently demonstrate end-to-end AI prototypes.
- Investigate and resolve failures: Debug issues across data, models, prompts, retrieval, APIs, infrastructure and application logic, identifying and addressing root causes.




- Collaborate and contribute: Participate in architecture discussions, communicate risks and dependencies, support engineers and research emerging AI approaches.

Required Skills

- Strong Python proficiency and experience writing clean, maintainable, testable production code.
- Solid foundations in Machine Learning, Deep Learning, NLP and Transformers, with hands-on experience in PyTorch or TensorFlow and Hugging Face.
- Practical experience with LLMs, SLMs, RAG, embeddings, vector databases, prompt engineering and LLM evaluation.
- Understanding of model architectures, tokenization, attention, context management, inference behaviour and model limitations.
- Experience with model adaptation and optimization approaches such as LoRA, QLoRA, PEFT, instruction tuning, quantization or distillation.
- Backend development using FastAPI, Flask or Django, with REST APIs, databases, asynchronous processing, authentication, RBAC and third-party integrations.
- Working knowledge of SQL/PostgreSQL, Git, Docker and Linux.
- Ability to independently review, debug and take ownership of implementations, including code generated using AI-assisted tools.

Preferred Skills

- AI orchestration: LangGraph, LangChain or equivalent frameworks.
- Model serving and infrastructure: vLLM, Triton, TGI, TensorRT-LLM, GPU deployment, Kubernetes and cloud, private cloud or on-premise environments.
- MLOps and evaluation: MLflow, Kubeflow, Airflow, DVC, RAGAS, DeepEval, LangSmith, promptfoo or equivalent tools.
- Application development: Redis, Celery, WebSockets, React/Next.js, JavaScript/TypeScript and HTML/CSS.
- Exposure to Speech-to-Text, Conversational AI, Voice AI, Computer Vision, Recommendation Systems or Multimodal AI.

Experience & Working Approach

- Demonstrated ownership of AI solutions from PoC to production; experience supporting real production users is strongly preferred.
- Strong research, debugging and communication skills, with the ability to work independently and collaborate across teams.
- Candidates with different experience levels may be considered where they demonstrate exceptional technical depth and ownership.

📌 AI Engineer (Hyderabad)
🏢 Aptagrim
📍 Hyderabad