# Senior Applied AI Engineer

> Weekday AI · Bengaluru, India · Full-time · Posted 2026-10-19

**Salary:** INR 3,800,000–5,500,000

**Workplace:** on_site

**Department:** Weekday's Client via platform

## Description

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.

## Apply

[Apply at Weekday AI](https://apply.workable.com/weekday-1/j/8C5964D7DE/apply)

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