AI Engineer – Generative AI & Agentic AI

Dicetek LLC; Bengaluru; On-site; INR 4,000,000 - 6,500,000; Full time

Job summary

Dicetek LLC is seeking an experienced AI Engineer to design, develop and deploy Generative AI and Agentic AI solutions for enterprise-scale use cases. You will build AI-powered applications and autonomous agents, coordinating with cross-functional teams across architecture, engineering, product, and business functions.

The role requires hands-on expertise with LangChain, Semantic Kernel, AutoGen, and cloud services (AWS/Azure) in Kubernetes-based environments.

Qualifications

• Senior professional with around 10 years of software engineering and cloud/platform experience.
• 3+ years hands-on AI engineering, incl Generative AI and LLM delivery.
• Strong Python with NumPy, pandas and FastAPI; experience with PyTorch or TensorFlow.
• Hands-on with LangChain, LangGraph; MS Semantic Kernel and MS AutoGen.
• Experience with RAG, embeddings, vector databases, semantic search and model eval.
• Deploying models on Bedrock, Azure OpenAI Service and Vertex AI.
• Experience with microservices, containers, APIs and event-driven/cloud-native patterns.
• Deploying AI workloads on Kubernetes in cloud/hybrid environments.
• Experience with CI/CD tools and DevOps toolchains; Jira tagging and release governance.

Responsibilities

• Design, develop, and deploy Generative AI and Agentic AI solutions for enterprise-scale use cases.
• Build intelligent systems that integrate backend services and client-facing apps across web, mobile, and enterprise platforms.
• Lead autonomous agents and multi-agent workflows in collaboration with architecture, engineering and product teams.

Skills

Generative AI

Agentic AI

Autonomous agents

Multi-agent orchestration

LLMs

Embeddings

Vector databases

RAG

Semantic search

Model evaluation

Guardrails

Observability

AI governance

Semantic Kernel

AutoGen

LangChain

LangGraph

Python

FastAPI

PyTorch

TensorFlow

REST APIs

Microservices

Serverless functions

Event-driven integration

Azure

AWS

Kubernetes

CI/CD

Jenkins

GitLab

Education

Bachelor’s degree in Computer Science, Software Engineering, Information Technology, Data Science, Artificial Intelligence or related

Tools

Jenkins

GitLab

Job description

Qualifications & Experience

We are looking for an experienced AI Engineer responsible for designing, developing, and deploying Generative AI and Agentic AI solutions that support enterprise-scale business use cases. The role will build intelligent systems that integrate complex backend services and client-facing applications across web, mobile and enterprise platforms.

The primary responsibility is to design and develop AI-powered applications, autonomous agents and multi-agent workflows while coordinating with cross-functional teams across architecture, engineering, product and business functions. A commitment to collaborative problem solving, sophisticated design and product quality is essential.

This role requires strong hands-on engineering experience, practical working knowledge of modern agent frameworks, and the ability to deliver secure, scalable, observable and governed AI solutions in cloud-native environments.

Minimum Qualification

• Bachelor’s degree in Computer Science, Software Engineering, Information Technology, Data Science, Artificial Intelligence or a related discipline.
• Relevant cloud, AI engineering, machine learning or architecture certifications are preferred.

Minimum Experience

• Senior professional with around 10 years of total software engineering, architecture, cloud or platform engineering experience.
• Minimum 3+ years of relevant hands-on AI Engineering experience, including Generative AI and practical LLM-based application delivery.
• Strong proficiency in Python, including NumPy, pandas, FastAPI and hands-on experience with PyTorch or TensorFlow.
• Hands-on experience with LangChain and LangGraph; mandatory working experience with Microsoft Semantic Kernel and Microsoft AutoGen.
• Experience implementing RAG using embeddings, vector databases, semantic search, retrieval optimization and model evaluation techniques.
• Experience deploying and managing models using Amazon Bedrock, Azure OpenAI Service and Google Vertex AI.
• Hands-on experience with microservices, containers, APIs, event-driven architecture, cloud-native services and evolutionary architecture practices.
• Experience managing and deploying AI workloads on Kubernetes in cloud-native and/or hybrid environments.
• Experience with CI/CD tools such as Jenkins or GitLab, DevOps toolchains, configuration management and cloud/on-prem deployment pipelines.
• Experience setting up pipelines with static code analysis, requirement tagging in Jira, quality gates and release governance.
• Experience operating monitoring tools for traditional infrastructure, cloud environments and AI-enabled business applications.
• Strong hands-on problem-solving mindset with the ability to analyze trade-offs and deliver sustainable, secure and high-quality solutions.

Key Technical Skills

• Generative AI, Agentic AI, autonomous agents, multi-agent orchestration and workflow-based AI systems.
• LLMs, embeddings, vector databases, RAG, semantic search, model evaluation, guardrails, observability and AI governance.
• Semantic Kernel, AutoGen, LangChain, LangGraph and similar agent frameworks.
• Python, FastAPI, PyTorch/TensorFlow, REST APIs, microservices, serverless functions and event-driven integration.
• Azure, AWS, Kubernetes, containers, CI/CD, DevOps automation, monitoring and secure software delivery.

Behavioural / Leadership Skills

• Strong collaborative mindset for agile architecture and decentralized decision making.
• Proactive, positive and growth-oriented leadership style with the ability to motivate engineers and foster craftsmanship.
• Strong communication, stakeholder engagement and influencing skills across product, business, architecture and engineering teams.
• Analytical, system-thinking and pragmatic problem-solving approach with commitment to product quality.