AI Engineer

Saksoft; Dadri, Chennai, Bengaluru; Hybrid; INR 1,200,000 - 1,800,000; Full time

Job summary

Saksoft is seeking a hands-on software engineer with 6+ years of experience to work on client-facing projects across application development, GenAI, cloud, and platform engineering. You will contribute reusable accelerators to the CoE and collaborate with Architects, AI Engineers, DevOps, and Cloud teams.

The role involves building APIs, microservices, and deploying on AWS/Azure/GCP, with a strong emphasis on security, CI/CD, and observability. Hybrid work model preferred.

Qualifications

• 6+ years of software/application development experience.
• Proficiency in Python and/or Java, .NET or Node.js.
• Experience with REST APIs and microservices.

Responsibilities

• Build and deliver client-facing applications and engineering solutions.
• Work with client teams to understand requirements and turn them into working solutions.
• Develop APIs, microservices, integrations and cloud-native applications.
• Build and integrate GenAI solutions such as LLM applications, RAG pipelines, AI agents and model APIs.
• Create PoCs, reusable components and accelerators for the CoE.
• Deploy and run solutions on AWS, Azure or GCP.
• Support CI/CD, containerization, deployment automation, monitoring and observability using Docker, Kubernetes and modern DevOps practices.
• Troubleshoot application, integration, cloud and deployment issues.
• Contribute to platform engineering and automation initiatives.
• Follow engineering, security, coding and architecture standards.
• Collaborate with Technical Architects, AI Engineers, DevOps, Cloud, Data and Platform teams.

Skills

Python

Java

.NET

Node.js

REST APIs

Microservices

Docker

Kubernetes

CI/CD

Cloud

GenAI

LLM

RAG

AI Agents

IAM/OAuth/SSO/RBAC

Monitoring

Git

Tools

Git

SQL

NoSQL

Vector databases

Job description

Location:Any Saksoft Location/ Hybrid

Experience: 6+ years

About the role
We are looking for a hands-on engineer who enjoys building real solutions and working directly with clients. You will work on client-facing engineering projects and also contribute reusable solutions and accelerators to our Centre of Excellence (CoE). The role spans application development, AI/GenAI, cloud, DevOps and platform engineering.

What you will do

• Build and deliver client-facing applications and engineering solutions
• Work with client teams to understand their requirements and turn them into working solutions
• Develop APIs, microservices, integrations and cloud-native applications
• Build and integrate GenAI solutions such as LLM applications, RAG pipelines, AI agents and model APIs
• Create PoCs, reusable components and accelerators for the CoE
• Deploy and run solutions on AWS, Azure or GCP
• Support CI/CD, containerization, deployment automation, monitoring and observability using Docker, Kubernetes and modern DevOps practices
• Troubleshoot application, integration, cloud and deployment issues
• Contribute to platform engineering and automation initiatives
• Follow engineering, security, coding and architecture standards
• Collaborate with Technical Architects, AI Engineers, DevOps, Cloud, Data and Platform teams

What we are looking for

• 5-7 years of software/application development experience with strong hands-on coding
• Proficiency in Python and/or Java, .NET or Node.js
• Experience with REST APIs and microservices
• Experience building and deploying enterprise applications
• Hands-on exposure to at least one cloud platform (AWS / Azure / GCP)
• Working knowledge of Docker, Kubernetes and CI/CD
• Experience with SQL and NoSQL databases and Git
• Experience with, or strong interest in, GenAI engineering: LLM applications, RAG, vector databases and AI agents
• Basic understanding of security concepts such as IAM, OAuth, SSO and RBAC
• Exposure to monitoring and observability tools
• Comfort working directly with client teams and solving problems across development, integration, deployment and support

Ideal profile
An engineer who can code, build PoCs, integrate systems, troubleshoot deployments and contribute to scalable, reusable solutions.