Senior Developer AI Offline

Responsibilities

• Design and develop scalable AI-powered applications and services, integrating

multi-agent frameworks and LLM-based workflows to enable intelligent

automation.

• Build and optimize AI models, vector search systems, and embeddings to

enhance data retrieval, analytics, and decision-making.

• Implement advanced API integrations, ensuring seamless interaction between AI

models, enterprise systems, and external data sources.

• Architect and manage AI cloud infrastructure on Azure (e.g., ACI, AKS),

prioritizing security, scalability, cost optimization and reliability for AI workloads.

• Lead the development of data pipelines for processing, storing, and retrieving

structured and unstructured data eJiciently.

• Supervise and mentor junior developers, ensuring best practices in AI workflow

development, API design/integrations, and cloud deployments.

• Automate infrastructure and model deployment with DevOps practices and

CI/CD pipelines

• Continuously monitor and optimize AI-driven applications, addressing

performance bottlenecks and improving system resilience through proactive

logging, real-time analytics, and comprehensive reporting to drive insights and

improvements.

• Collaborate with architects and product managers to define AI strategies,

aligning technical solutions with business objectives.

• Research and integrate emerging AI technologies, keeping the platform current,

competitive, and future-proof.

Senior Developer Skills

• Minimum 10 years of software engineering experience spanning design,

development, testing, and deployment.

• Enterprise integration background with hands-on experience in developing and

integrating REST/SOAP web services, managed APIs, OAuth 2 authentication,

and messaging queues for reliable system communication.

• Strong experience coding in Python or C#, plus JavaScript/TypeScript, SQL, and a

solid grasp of design and integration patterns.

Classifica(on: Internal• Hands-on experience with agentic workflows and multi-agent frameworks (e.g.,

Autogen/AG2, LangChain/LangGraph, CrewAI) to orchestrate AI agents.

• Advanced knowledge of Retrieval-Augmented Generation (RAG) and prompt

engineering (ReAct, Reflection, chain-of-thought) and Metacognitive AI

techniques.

• Familiarity with vector embeddings, semantic search, and vector databases

(Pinecone, FAISS) for AI-powered information retrieval.

• Solid understanding of AI/ML fundamentals (pre-training, fine-tuning, transfer

learning, Transformers) and LLM architectures, including parameter scaling.

• Strong expertise in Azure AI and cloud services, designing modular AI

architectures with Azure AI Services and data processing pipelines.

• Proven expertise in entity and data modeling, with hands-on experience in

relational, NoSQL, and vector databases, optimizing data pipelines to support AI

applications eJiciently.

Preferred Qualifications

• Proficiency in Python or C#, with working knowledge of JavaScript/TypeScript

and SQL.

• Robust enterprise integration experience, developing complex orchestrations

involving service chaining, content-based routing, and guaranteed delivery.

• Practical experience with data pipelines, Azure Data Factory, Azure SQL Server,

and Microsoft Fabric, with a strong understanding of data warehouses, data

lakes, and data lakehouses, including their architectures, use cases, and best

practices for managing large-scale data workloads in AI-driven applications

• Azure AI Engineer Associate, Azure Data Scientist Associate, or similar

certification, plus hands-on knowledge of Azure Functions, ACI, Azure AI

Services, Azure OpenAI, and KQL.

• Familiarity with DevOps principles and CI/CD pipelines for automating AI model

and software deployments.

• Tertiary qualification in Software Engineering, Computer Science, or a related

field.