Senior Applied AI Engineer

𝗧𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗳𝗼𝗿 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝗲𝗸𝗱𝗮𝘆'𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀

𝗦𝗮𝗹𝗮𝗿𝘆 𝗿𝗮𝗻𝗴𝗲: 𝗥𝘀 𝟯𝟴𝟬𝟬𝟬𝟬𝟬 - 𝗥𝘀 𝟱𝟱𝟬𝟬𝟬𝟬𝟬 (𝗶𝗲 𝗜𝗡𝗥 𝟯𝟴-𝟱𝟱 𝗟𝗣𝗔)

Experience: 4+ yrs

Location: Bangalore

We are looking for a highly skilled Senior Applied AI Engineer to build and scale production-grade AI systems that enable intelligent, reliable, and personalized healthcare experiences. This role combines applied AI, LLM engineering, backend development, agentic workflows, clinical reasoning, and AI safety to deliver technology that improves healthcare accessibility and user outcomes.

The ideal candidate will have strong Python and backend engineering expertise, hands-on experience deploying AI systems in production, and the ability to solve complex problems in high-stakes environments. You will help transform advanced AI capabilities into dependable healthcare products with measurable performance, safety, and reliability.

Requirements

Key Responsibilities

• Design and deploy AI-powered clinical workflows that reason across patient history, symptoms, medications, lab reports, and relevant medical information.
• Build agentic AI architectures and multi-agent systems for clinical reasoning, information retrieval, verification, risk assessment, and escalation.
• Develop backend services, APIs, data pipelines, and model orchestration systems using Python and modern engineering frameworks.
• Build scalable RAG pipelines that retrieve relevant information from trusted medical sources, clinical guidelines, prescriptions, and patient health records.
• Implement prompt engineering, context management, model routing, verifier layers, and uncertainty detection to improve response quality.
• Develop comprehensive AI evaluation frameworks, including simulated-patient testing, regression benchmarks, red-team scenarios, and clinical safety metrics.
• Measure and improve clinical accuracy, hallucination risk, escalation quality, empathy, response relevance, and overall system reliability.
• Implement safety mechanisms for high-risk situations, including emergency escalation, human review, uncertainty handling, and fail-safe behaviour.
• Build AI features for web, mobile, messaging, and other digital healthcare experiences.
• Improve the processing of unstructured and complex inputs, including PDFs, laboratory reports, prescriptions, incomplete medical histories, and longitudinal patient context.
• Optimise AI systems for latency, scalability, cost efficiency, monitoring, and production stability.
• Diagnose and resolve issues across application, model, data, and infrastructure layers.
• Collaborate with clinicians, medical reviewers, product teams, and engineers to translate clinical judgement into reliable software.
• Establish best practices for AI testing, privacy, observability, auditability, and continuous deployment.

What Makes You a Great Fit

• 4+ years of relevant experience, with strong hands-on expertise in production software engineering and applied AI.
• Strong proficiency in Python and backend application development.
• Proven experience building and deploying production-grade LLM, machine learning, or data-intensive systems beyond experimental prototypes.
• Strong understanding of APIs, distributed systems, testing, monitoring, and production reliability.
• Practical experience with RAG, prompt and context engineering, AI agents, model routing, fine-tuning, evaluation, or model deployment.
• Familiarity with frameworks and technologies such as FastAPI, PyTorch, TensorFlow, LangGraph, LangChain, LlamaIndex, vector databases, and LLM observability tools.
• Strong analytical and problem-solving skills, with the ability to navigate ambiguous technical challenges.
• High product ownership and sound judgement when balancing accuracy, user experience, safety, performance, and cost.
• Ability to collaborate effectively with engineering, product, and clinical stakeholders.
• Excellent written and verbal communication skills, including the ability to explain complex technical trade-offs clearly.
• A strong commitment to responsible AI, privacy, clinical safety, and measurable production quality.