AI ML Engineer (7+ Years)

• Notice Period: Immediate joiners Number of Openings: 1 Working hours : 3 PM – 12 AM IST Job Summary We are seeking a Senior Python Developer who excels at building scalable, AI-integrated systems using modern tools and frameworks. The ideal candidate embraces AI-assisted development (GitHub Copilot, ChatGPT, AutoGen, etc.) to boost productivity, improve code quality, and drive innovation across our application stack. This role combines backend expertise, cloud-native architecture, and hands-on AI integration to deliver intelligent, high-performance solutions. Key Responsibilities AI Model Integration & Optimization • Integrate APIs from multiple AI platforms (OpenAI, Anthropic, Gemini, Llama, Mistral, etc.) into scalable backend systems. • Build multi-model orchestration layers balancing cost, latency, and accuracy. • Fine-tune prompts, manage context windows, and implement RAG (Retrieval-Augmented Generation) solutions for domain-specific use cases. • Optimize token usage, caching, and filtering strategies to enhance system efficiency and user experience. Application & System Development • Design and implement AI-enabled workflows seamlessly integrated with web, mobile, or enterprise ecosystems. • Develop Python-based backends and APIs using frameworks like FastAPI, Flask, or Django. • Build and deploy microservices and cloud-native services leveraging Docker, Kubernetes, and serverless architectures • Collaborate with frontend, DevOps, and product teams to ensure smooth feature delivery and deployment. • Monitor and evaluate AI responses through metrics, evaluation frameworks, or RLHF-inspired feedback loops. • Implement AI guardrails for responsible usage including bias detection, toxicity filtering, and compliance enforcement. • Debug and resolve performance or reliability issues in AI-powered production systems. Innovation & Collaboration • Stay up to date with the evolving AI model landscape, exploring new models, APIs, and orchestration frameworks. • Experiment with multi-modal AI (vision, text, speech) for applicability in client scenarios. • Work closely with cross-functional teams to translate business goals into intelligent, automated features. Primary Skills • Python backend expert: FastAPI, async I/O, API design, testing. • Production LLM integration: OpenAI/Anthropic/Gemini/Mistral; prompt and context strategies; RAG with a vector DB. • Cloud-native delivery: Docker, AWS (preferred), CI/CD, IaC basics (Terraform or Pulumi). • Data layer: SQL (PostgreSQL), caching/queues (Redis + Celery/RQ/SQS/Kafka). • Daily AI-assisted development (Copilot/Others) for coding and tests. Required Skills & Qualifications • Expert in Python backend development with hands-on experience integrating AI models, building cloud-native microservices, and using AI-assisted coding tools for faster, smarter development. • Proven hands-on experience integrating LLM APIs (OpenAI, Claude, Gemini, Llama, etc.). • Strong expertise in AI/ML frameworks (TensorFlow, PyTorch, scikit-learn, Hugging Face, etc.)" as essential qualification • Practical knowledge of LangChain, LlamaIndex, Codium or similar frameworks for AI workflow orchestration. • Understanding of prompt engineering, embeddings, vector databases (Pinecone, Weaviate, FAISS, pgvector), and RAG pipelines. • Strong background in cloud platforms (AWS, GCP, Azure), containerization, and orchestration. • Deep understanding of REST/GraphQL APIs, async programming, task queues, and caching mechanisms. • Familiarity with SQL/NoSQL databases (PostgreSQL, MongoDB, Redis). • Experience using AI-assisted tools such as GitHub Copilot, ChatGPT API, AutoGen, or OpenDevin for coding and testing automation. • Exposure to CI/CD pipelines and Infrastructure as Code (Terraform, Pulumi). • Knowledge of data preprocessing, NLP/NLU, and model evaluation techniques. • Data Engineering & Processing, Data pipeline development , ETL/ELT processes, Batch processing and stream processing frameworks, Large-scale data handling with pandas, NumPy, Dask Preferred Skills • Hands-on with multi-modal AI (vision, text-to-speech, speech-to-text). • Experience with MLOps practices including CI/CD for AI pipelines, model monitoring, and drift detection. • Background in fine-tuning, reinforcement learning, or custom model training. • Familiarity with enterprise security standards (GDPR, HIPAA, SOC2). • Contributions to open-source or personal AI-assisted coding initiatives. Soft Skills • Excellent problem-solving and analytical thinking ability. • Strong cross-functional collaboration and communication skills. • Clear technical documentation habits. • Curious, experimental mindset with a drive to explore the next frontier in AI-driven development.