Senior Software Engineer, AI Applications

Experity; Bengaluru; On-site; INR 3,000,000 - 5,400,000; Full time

Job summary

Experity is seeking an experienced AI Software Engineer to design, develop, and maintain production-grade AI-powered applications. You will build solutions using LLMs, vector databases, embeddings, and agent frameworks, implementing RAG architectures and guardrails for reliability.

You will contribute to product integration, APIs, microservices, and cloud-native workloads, while mentoring teammates and upholding engineering standards. Experience with cloud platforms and AI tools is essential.

Qualifications

• Bachelor's degree in Computer Science, Software Engineering, or related field, or equivalent practical experience.
• 5+ years of professional software engineering experience.
• 2+ years developing AI, machine learning, or generative AI applications.
• Strong proficiency in Python, TypeScript, Java, or C#.
• Experience building and deploying cloud-native applications on AWS, Azure, or Google Cloud.
• Experience with RESTful APIs, distributed systems, and microservice architectures.
• Hands-on experience with LLMs and AI platforms like OpenAI, Anthropic, Azure OpenAI, Google Gemini, or similar.
• Experience implementing RAG, vector databases, and semantic search.
• Knowledge of CI/CD, DevOps, and software development lifecycle.
• Excellent problem-solving, communication, and collaboration skills.

Responsibilities

• Design, develop, and maintain production-grade AI-powered applications and services.
• Build and integrate solutions leveraging LLMs, generative AI platforms, vector databases, embeddings, and agent frameworks.
• Implement Retrieval-Augmented Generation (RAG) architectures and knowledge retrieval systems.
• Develop prompt engineering strategies, evaluation frameworks, and guardrails to improve AI quality and reliability.
• Integrate AI capabilities into existing products, workflows, and business processes.
• Design scalable, secure, and maintainable software systems with modern engineering practices.
• Develop APIs, microservices, and cloud-native applications supporting AI workloads.
• Create reusable frameworks and components that accelerate AI product development.
• Ensure solutions meet performance, reliability, observability, and security standards.
• Participate in architecture reviews and technical design discussions.
• Evaluate, benchmark, and optimize AI models and providers for quality, latency, and cost.
• Collaborate with data and platform teams to manage AI infrastructure and deployment pipelines.
• Mentor engineers and drive technical growth and best practices.

Skills

Problem solving

Communication

Collaboration

Code quality

Technical leadership

Problem solving

Education

Bachelor's degree in Computer Science or related field

Tools

Python

TypeScript

Java

C#

AWS

Azure

Google Cloud

RESTful APIs

Distributed systems

Microservices

Kubernetes

OpenAI / Anthropic / Azure OpenAI

Vector databases

LangChain

RAG

Job description

• Design, develop, and maintain production-grade AI-powered applications and services.
• Build and integrate solutions leveraging LLMs, generative AI platforms, vector databases, embeddings, and agent frameworks.
• Implement Retrieval-Augmented Generation (RAG) architectures and knowledge retrieval systems.
• Develop prompt engineering strategies, evaluation frameworks, and guardrails to improve AI quality and reliability.
• Integrate AI capabilities into existing products, workflows, and business processes.

Key Responsibilities

• Design, develop, and maintain production-grade AI-powered applications and services.
• Build and integrate solutions leveraging LLMs, generative AI platforms, vector databases, embeddings, and agent frameworks.
• Implement Retrieval-Augmented Generation (RAG) architectures and knowledge retrieval systems.
• Develop prompt engineering strategies, evaluation frameworks, and guardrails to improve AI quality and reliability.
• Integrate AI capabilities into existing products, workflows, and business processes.

AI Application Development

• Design, develop, and maintain production-grade AI-powered applications and services.
• Build and integrate solutions leveraging LLMs, generative AI platforms, vector databases, embeddings, and agent frameworks.
• Implement Retrieval-Augmented Generation (RAG) architectures and knowledge retrieval systems.
• Develop prompt engineering strategies, evaluation frameworks, and guardrails to improve AI quality and reliability.
• Integrate AI capabilities into existing products, workflows, and business processes.

Software Engineering & Architecture

• Design scalable, secure, and maintainable software systems using modern engineering practices.
• Develop APIs, microservices, and cloud-native applications supporting AI workloads.
• Create reusable frameworks and components that accelerate AI product development.
• Ensure solutions meet performance, reliability, observability, and security standards.
• Participate in architecture reviews and technical design discussions.

AI Operations & Model Management

• Evaluate, benchmark, and optimize AI models and providers for quality, latency, and cost.
• Implement monitoring, logging, testing, and observability for AI systems. Establish processes for model evaluation, prompt versioning, and continuous improvement.
• Collaborate with data and platform teams to manage AI infrastructure and deployment pipelines.

Collaboration & Leadership

• Partner with product management to identify and prioritize AI opportunities.
• Mentor engineers and contribute to team-wide technical growth.
• Drive engineering best practices, code quality, and architectural standards.
• Participate in code reviews and provide technical leadership on complex initiatives.
• Communicate technical concepts effectively to both technical and non-technical stakeholders.

Required Qualifications

• Bachelor's degree in Computer Science, Software Engineering, or related field, or equivalent practical experience.
• 5+ years of professional software engineering experience.
• 2+ years developing AI, machine learning, or generative AI applications.
• Strong proficiency in one or more modern programming languages such as Python, TypeScript, Java, or C#.
• Experience building and deploying cloud-native applications on AWS, Azure, or Google Cloud.
• Experience with coding harnesses
• Experience with RESTful APIs, distributed systems, and microservice architectures.
• Hands-on experience with LLMs and AI platforms such as OpenAI, Anthropic, Azure OpenAI, Google Gemini, or similar.
• Experience implementing RAG solutions, vector databases, and semantic search.
• Strong understanding of software development lifecycle, CI/CD, testing, and DevOps practices.
• Excellent problem-solving, communication, and collaboration skills.

Preferred Qualifications

• Experience with agentic AI frameworks such as Strands, LangChain, LangGraph, Semantic Kernel, CrewAI, or similar.
• Experience with vector databases such as Pinecone, Weaviate, Qdrant, Chroma, or Azure AI Search.
• Familiarity with MLOps and AI evaluation frameworks.
• Experience deploying AI workloads using Kubernetes and containerized environments.
• Knowledge of AI governance, security, compliance, and responsible AI practices.
• Experience in healthcare, fintech, SaaS, or other regulated industries.
• Contributions to open-source AI projects or technical communities.

Equal Opportunity Employer This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.