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AI Engineer

Inlogic Technologies
Chennai, Tamil Nadu

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Job details

Full-time

Qualifications

BCS
CI/CD
Azure
Law
Computer Science
MCP
Kubernetes
C#
Google Cloud Platform
.NET
Databases
OS Kernels
AWS
Docker
Bachelor's degree
Continuous integration
Deep learning
Natural language processing
APIs
Data science
AI
Communication skills
Python
Data Science

Full job description

Job Type: Full-time

Job Location: Chennai

Experience: 1.6 Years

About Us

We’re building an AI centre of excellence to deliver cutting-edge AI development and consulting services. As we scale, we’re seeking passionate Entry Level AI Engineers to join our team, working with senior architects to prototype, deploy, and consult on AI-powered solutions across industries.

What You’ll Do

Assist in the design and prototyping of AI solutions using LLMs (e.g., GPT-4, Claude, Gemini) and retrieval augmented generation.
Build and integrate AI agents with frameworks like LangChain, Semantic Kernel, or Hugging Face Agents.
Support ML and MLOps pipelines using AWS SageMaker, Azure AI Services, and Google Vertex AI
Deploy AI models to onpremises or cloud environments, including MCP servers.
Collaborate with senior engineers to scale and productionize AI services for consulting clients.
Monitor model performance, troubleshoot issues, and iterate rapidly.
Stay informed on advances in GenAI, AI agents, multimodal models, and AI infrastructure.
Help create demos, technical collateral, and internal/external training materials.

Requirements Essential:

Bachelor’s degree in computer science, Engineering, Data Science, or equivalent experience.
Solid programming skills in Python, and preferably familiarity with C#/.NET.
Foundational understanding of AI/ML concepts, deep learning, NLP, and LLMs.
Experience or coursework with at least one cloud AI platform: AWS, Azure, or Google Cloud
Knowledge of LLM APIs and agent frameworks.
Familiarity with MCP server environments and cloud on prem configurations.
Good problem-solving aptitude, communication skills, and eagerness to learn.

Nice to Have:

Practical experience with Docker, Kubernetes, or container orchestration.
Understanding of vector databases (e.g., Pinecone, Weaviate) and vector search.
Exposure to prompt engineering and RAG systems.
Familiarity with MLOps tools and CI/CD workflows for AI
Certifications in Azure AI Engineer, AWS ML Specialty, or GCP Engineer tracks.

What You’ll Gain:

Access to cutting-edge AI tools, sandboxes, and cloud environments.
Rapid upskilling through hands-on projects, workshops, and certifications.
A role at the forefront of enterprise AI adoption and innovation.

We’d love to know your experience with LLMs, cloud AI, or agent frameworks—even at a prototype stage.

Apply Now

Ready to take the next step in your Career ?

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