senior expert, it development

Randstad Staffing; Pune District; On-site; INR 2,500,000 - 3,500,000; Full time

Benefits offered by this job

Opportunity to influence engineering culture

Work with experienced teams

Build scalable systems

Job summary

Randstad Staffing is looking for a Senior Expert to lead the design and implementation of complex AI solutions integrated with enterprise-grade applications in Pune, India. This pivotal role requires a deep technical understanding, as well as leadership to bridge AI research and business needs.

The ideal candidate will possess over 15 years of software engineering experience, specializing in distributed architectures and ensure innovation aligns with business strategies. Candidates should demonstrate a commitment to quality and best practices while fostering a culture of creativity.

Qualifications

• 15+ years in software engineering with expertise in distributed architectures.
• Hands-on experience in LLM orchestration and RESTful API development.
• Proficiency in data management for production-grade model deployment.

Responsibilities

• Lead design of AI agents and orchestration layers.
• Oversee integration of AI components into enterprise systems.
• Ensure compliance with quality and security standards.

Skills

Software engineering

Python (FastAPI, PyTorch, TensorFlow)

Java (Spring Boot)

LLM orchestration (LangChain, LlamaIndex)

Data architecture and RDBMS

MLOps

Containerized deployments (Docker/Kubernetes)

Cloud computing (AWS/Azure/GCP)

OAuth2, JWT, security protocols

Education

Master's degree in Computer Science or related field

Tools

Docker

Kubernetes

FastAPI

PyTorch

TensorFlow

Spring Boot

Job description

We are seeking a Senior Expert with technical depth to own the architecture, design, and implementation of high‑complexity RAG and Agentic AI solutions integrated with enterprise middleware and a robust microservices ecosystem. This role bridges the gap between cutting‑edge AI research and robust, scalable enterprise applications, ensuring technical standards and innovation align with business strategy.

Key Responsibilities and Scope

• Lead the high‑level design of AI agents and orchestration layers using frameworks like LangChain or LlamaIndex to solve complex business problems.
• Direct the development and optimization of Retrieval‑Augmented Generation pipelines, ensuring efficient embeddings, vector search, and retrieval workflows.
• Oversee the integration of AI components into enterprise orchestration layers and business systems via secure RESTful APIs and microservices.
• Act as the ultimate technical escalation point, fixing complicated errors and resolving complex integration issues within the AI workload.
• Implement and champion technical standards, methods, and best practices for AI code quality, testing, and documentation across projects.
• Advise senior leadership on the feasibility and complexity of new AI products, influencing the development roadmap to meet technology strategies.
• Establish frameworks for evaluating, benchmarking, and monitoring models using standard metrics and observability tools.
• Lead project‑based teams through the full development lifecycle of high‑complexity AI software or infrastructure deliverables.
• Partner with Product, DevOps, Security, and Data teams to ensure end‑to‑end delivery of complex AI‑enabled platforms.
• Identify quality and security risks in AI architectures and ensure compliance with enterprise policies and OWASP standards.
• Foster a development culture that supports creativity and rapid prototyping while maintaining high‑quality, predictable delivery.

Required Skills & Experience

• 15+ years in software engineering with specialized expertise in designing solutions of high complexity and scale in distributed architectures.
• In‑depth proficiency in Python (FastAPI, PyTorch, TensorFlow) or Java (Spring Boot) for enterprise‑grade application development.
• Hands‑on experience in LLM orchestration (LangChain, LlamaIndex) and vector databases, along with knowledge in RESTful API development and integrating AI/ML services into complex middleware and web platforms.
• Ability to convert complex technical information into compelling business context for non‑technical stakeholders.
• Proficiency in data architecture, RDBMS, and managing data pipelines for production‑grade model deployment.
• Strong understanding of MLOps, containerized deployments (Docker/Kubernetes), CI/CD pipelines, and cloud computing (AWS/Azure/GCP).
• Deep understanding of OAuth2, JWT, and security protocols required for enterprise AI applications.
• Master’s degree in Computer Science, Software Engineering, or a related field, or equivalent high‑level experience.

Preferred Experience

• Proven experience building orchestrated AI workflows or multi‑agent systems in a production environment.
• Practical experience with managed platforms such as GCP Vertex AI, AWS Bedrock, or Azure OpenAI.
• Experience in MLOps, model lifecycle management, and cost optimization for high‑scale AI workloads.
• History of working with event‑driven systems or integrating AI features into legacy enterprise applications.
• Active contributions to open‑source AI/ML projects or custom developer toolkits.

Leadership Competencies

• Ability to guide others and set the direction for a job discipline without needing direct management authority.
• Strong negotiation and relationship management skills to align technical delivery with customer and business objectives.
• Strong analytical skills with the ability to work independently in the most complex, dynamic situations.
• Self‑driven passion for staying updated on rapidly evolving trends in AI frameworks and orchestration technologies.
• Passion for building high‑performing teams and commitment to fostering a diverse and equitable environment, valuing different perspectives to drive innovation.

Why Join Us

• Lead platforms that combine foundations (enterprise products) with modern capabilities (AI Agents, LLMs).
• Influence engineering culture, architecture, and tooling evolution.
• Work with experienced teams and a forward‑looking tech roadmap.
• Opportunity to build systems that scale both technically and organizationally.