AI Software Engineer
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Job Location:
Monthly Salary:
Posted on:
4 hours ago
Vacancies:
1 Vacancy
Job Summary
AI First System Design & Software Engineering
Apply strong software engineering principles to design build test deploy and operate AI powered systems.
Architect clean scalable and maintainable services using microservices and distributed system design patterns.
Own solutions end to end ensuring reliability observability security and maintainability in production.
Make informed engineering trade offs around scalability latency cost and fault tolerance.
Generative AI & Retrieval Augmented Generation (RAG)
Design and implement LLM based solutions for real world production use cases.
Apply deep hands on expertise in:
o Prompt engineering
o Chunking strategies for unstructured data
o Embeddings and vector databases
o Retrieval Augmented Generation (RAG)
o Graph RAG (knowledge graphs combined with vector search).
Ensure AI systems are robust explainable and production ready.
Agentic AI & Workflow Automation
Build Agentic AI systems capable of planning reasoning and executing multi step workflows.
Implement tool and function calling context management and memory strategies for agents.
Design systems where agents orchestrate workflows and LLMs act as reasoning and decision layers.
Identify opportunities to replace manual or rule based processes with AI driven automation.
Cloud Native AI Platforms & AWS
Build and deploy AI services on AWS using cloud native patterns.
Work hands on with AWS services such as:
o EC2 Lambda ECS EKS
o DynamoDB RDS (PostgreSQL/MySQL) MongoDB
o IAM VPC S3 EBS CloudFront Route 53.
Leverage AWS Bedrock (Agents Knowledge Bases) and Amazon SageMaker to operationalize AI solutions.
Containers DevOps & CI/CD
Containerize AI services using Docker and deploy using Kubernetes (EKS).
Integrate services into CI/CD pipelines using GitHub or GitLab.
Manage infrastructure using Infrastructure as Code (Terraform).
Ensure stable repeatable deployments in Linux environments.
Application Integration (Good to Have)
Contribute to backend or application integration when required:
o Backend: Python (Flask) or (Express)
o Frontend: React or Angular.
Integrate AI services with existing applications using APIs or events.
UI and full stack work is supportive not a primary responsibility.
Required Skills & Qualifications
5 years of experience in Software Engineering or AI Engineering.
Strong software engineering skills with proven experience building production systems.
Strong programming experience in Python.
Hands on experience with:
o Generative AI and Large Language Models
o RAG pipelines embeddings and vector databases
o Agentic AI workflows and systems.
Solid understanding of:
o System design
o Microservices and distributed systems.
Experience deploying and operating systems on AWS.
Comfortable working in Agile environments and Linux systems
Apply strong software engineering principles to design build test deploy and operate AI powered systems.
Architect clean scalable and maintainable services using microservices and distributed system design patterns.
Own solutions end to end ensuring reliability observability security and maintainability in production.
Make informed engineering trade offs around scalability latency cost and fault tolerance.
Generative AI & Retrieval Augmented Generation (RAG)
Design and implement LLM based solutions for real world production use cases.
Apply deep hands on expertise in:
o Prompt engineering
o Chunking strategies for unstructured data
o Embeddings and vector databases
o Retrieval Augmented Generation (RAG)
o Graph RAG (knowledge graphs combined with vector search).
Ensure AI systems are robust explainable and production ready.
Agentic AI & Workflow Automation
Build Agentic AI systems capable of planning reasoning and executing multi step workflows.
Implement tool and function calling context management and memory strategies for agents.
Design systems where agents orchestrate workflows and LLMs act as reasoning and decision layers.
Identify opportunities to replace manual or rule based processes with AI driven automation.
Cloud Native AI Platforms & AWS
Build and deploy AI services on AWS using cloud native patterns.
Work hands on with AWS services such as:
o EC2 Lambda ECS EKS
o DynamoDB RDS (PostgreSQL/MySQL) MongoDB
o IAM VPC S3 EBS CloudFront Route 53.
Leverage AWS Bedrock (Agents Knowledge Bases) and Amazon SageMaker to operationalize AI solutions.
Containers DevOps & CI/CD
Containerize AI services using Docker and deploy using Kubernetes (EKS).
Integrate services into CI/CD pipelines using GitHub or GitLab.
Manage infrastructure using Infrastructure as Code (Terraform).
Ensure stable repeatable deployments in Linux environments.
Application Integration (Good to Have)
Contribute to backend or application integration when required:
o Backend: Python (Flask) or (Express)
o Frontend: React or Angular.
Integrate AI services with existing applications using APIs or events.
UI and full stack work is supportive not a primary responsibility.
Required Skills & Qualifications
5 years of experience in Software Engineering or AI Engineering.
Strong software engineering skills with proven experience building production systems.
Strong programming experience in Python.
Hands on experience with:
o Generative AI and Large Language Models
o RAG pipelines embeddings and vector databases
o Agentic AI workflows and systems.
Solid understanding of:
o System design
o Microservices and distributed systems.
Experience deploying and operating systems on AWS.
Comfortable working in Agile environments and Linux systems
Key Skills
- Spring
- .NET
- C/C++
- Go
- React
- OOP
- C#
- Data Structures
- JavaScript
- Software Development
- Java
- Distributed Systems
