Senior Solutions Engineer

Eigenrisk; Bengaluru; Hybrid; INR 2,400,000 - 4,200,000; Full time

Job summary

Eigenrisk in Bengaluru seeks a Senior AI Solutions Engineer to design and implement scalable AI-powered product capabilities and intelligent automation systems.

You will work with product, engineering, analytics, and business teams to translate real-world requirements into robust AI solutions, shaping our AI engineering practices and accelerating delivery of next-generation AI products. You will mentor engineers, drive PoCs, and ensure reliability and observability of AI services in production.

Qualifications

• 5–7 years in software engineering or AI application development.
• Proficient in Python and backend/API development.
• Experience with LLM ecosystems and AI orchestration.
• Experience building cloud-native AI services.
• Strong debugging and system design skills.

Responsibilities

• Design, develop, and deploy AI-powered features and workflows.
• Lead MCP-compatible integrations and agentic AI systems.
• Architect scalable orchestration pipelines for AI services.
• Develop reusable AI components, APIs, and acceleration tools.
• Collaborate with product to define AI use cases and solutions.
• Mentor engineers and promote best practices within the AI team.
• Evaluate new AI frameworks and tools and platforms.
• Drive PoCs and productionize prototypes into production systems.
• Ensure reliability, scalability, observability of AI services.
• Collaborate with DevOps for deployment and operation of AI systems.
• Contribute to architectural discussions and platform evolution.

Skills

Python

Backend/API development

LLM ecosystems

AI orchestration

Cloud-native

System design

Problem-solving

Tools

LLM platforms

Kubernetes

API gateways

Cloud platforms

Job description

The Role

We are looking for a highly motivated and hands-on Senior AI Solutions Engineer to lead the design and implementation of scalable AI-powered product capabilities and intelligent automation systems.

The ideal candidate will have strong experience building production-grade AI applications, integrating LLM ecosystems, and developing intelligent workflows using modern orchestration and integration frameworks. This role will play a key part in shaping the companys AI engineering practices and accelerating delivery of next-generation AI solutions.

The position involves close collaboration with product, engineering, analytics, and business teams to translate real-world requirements into robust, scalable, and maintainable AI systems.

What You'll Do

• Design, develop, and deploy AI-powered product features and intelligent workflows
• Lead implementation of MCP-compatible integrations and agentic AI systems
• Architect scalable orchestration pipelines for AI services, tools, and automation frameworks
• Develop reusable AI engineering components, APIs, and integration accelerators
• Work closely with product teams to define AI use cases and technical solutions
• Mentor junior engineers and guide engineering best practices within the AI team
• Evaluate emerging AI frameworks, tooling, and platform capabilities
• Drive proof-of-concepts and rapidly transition successful prototypes into production systems
• Ensure reliability, scalability, observability, and performance of AI services
• Collaborate with DevOps and platform teams for deployment and operationalization of AI systems
• Contribute to technical architecture discussions and platform evolution

What We're Looking For

• 5-7 years of experience in software engineering, platform engineering, or AI application development
• Strong proficiency in Python and backend/API development
• Experience working with LLM ecosystems, AI orchestration frameworks, or intelligent automation platforms
• Familiarity with MCP, tool integrations, workflow engines, and API-first architectures
• Experience building scalable cloud-native applications and services
• Understanding of retrieval systems, prompt workflows, vector databases, and AI integrations
• Strong debugging, system design, and problem-solving skills
• Ability to work in fast-paced product engineering environments

Added Advantage

• Experience with multi-agent systems or agentic AI workflows
• Exposure to cloud platforms such as AWS, Azure, or GCP
• Experience with observability, monitoring, and AI evaluation frameworks
• Familiarity with CI/CD and production deployment practices
• Exposure to risk analytics, fintech, or enterprise SaaS environments

What Makes You a Great Fit

• Strong ownership mindset with a builder mentality
• Comfortable balancing experimentation with production readiness
• Passionate about emerging AI technologies and practical applications
• Able to independently drive technical initiatives end-to-end
• Strong communication and collaboration skills across technical and business teams