AI & Intelligent Automation Engineer

About the Company:

We are a global consulting firm; we specialize in transforming businesses through innovative digital solutions. Our expertise spans across Process Improvement, Business Process Outsourcing, AI & Automation Solutions, and Captive Setup Services. Please visit www.navsan.com

Role Overview

The ideal candidate combines strong software engineering capabilities with deep expertise in AI-powered automation platforms, enterprise integration, DevSecOps practices, and scalable cloud architectures. The engineer will work closely with cross-functional teams including AI architects, cloud engineers, cybersecurity specialists, infrastructure teams, and business stakeholders to deliver end-to-end automation solutions aligned with AIM (Advise, Implement, Manage) methodology.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or related field.
• 6+ years of experience in software engineering, automation engineering, or AI engineering roles.
• 3+ years of experience implementing enterprise automation solutions using AI/ML technologies.
• Strong programming skills in Python, Java, JavaScript, or C#.
• Experience with workflow automation and orchestration platforms.
• Hands-on experience with REST APIs, microservices, and event-driven architectures.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Strong understanding of DevOps, CI/CD, and Infrastructure as Code principles.
• Experience working with databases including SQL, NoSQL, and vector databases.

Preferred Skills

• Experience with Generative AI frameworks such as LangChain, Semantic Kernel, or LlamaIndex.
• Knowledge of LLM platforms including OpenAI, Azure OpenAI, Anthropic, or open-source LLMs.
• Experience with RPA platforms such as UiPath, Automation Anywhere, Power Automate.
• Familiarity with container orchestration technologies including Docker and Kubernetes.
• Understanding of cybersecurity best practices and secure automation design.
• Experience with observability and monitoring tools such as Prometheus, Grafana, ELK, or Splunk.
• Exposure to enterprise IT environments including hybrid cloud and data center modernization initiatives.
• AI governance, compliance, and responsible AI implementation knowledge.

Key Responsibilities

AI & Intelligent Automation Development

• Design and implement AI-driven automation workflows for enterprise business processes.
• Develop intelligent agents, copilots, chatbots, and workflow automation using Generative AI and LLM technologies.
• Build scalable automation pipelines integrating AI, analytics, and enterprise systems.
• Create reusable automation frameworks, APIs, and orchestration components.
• Implement document intelligence, OCR, NLP, and computer vision automation solutions.

Enterprise Automation & Integration

• Integrate automation solutions with enterprise platforms such as ERP, CRM, ITSM, cloud platforms, and data systems.
• Develop event-driven and API-based integrations using modern middleware and integration frameworks.
• Automate infrastructure provisioning, CI/CD pipelines, cloud operations, and monitoring workflows.
• Collaborate with infrastructure and cloud teams to modernize enterprise operations.

AI Engineering & Data Solutions

• Deploy and optimize machine learning and Generative AI models in production environments.
• Implement Retrieval-Augmented Generation (RAG), vector databases, semantic search, and AI orchestration frameworks.
• Fine-tune AI models and optimize prompt engineering strategies.
• Ensure responsible AI governance, model observability, and performance monitoring.

Cloud & DevSecOps Automation

• Build automation solutions across AWS, Azure, Google Cloud, and hybrid cloud environments.
• Implement Infrastructure as Code (IaC) using Terraform, Ansible, or CloudFormation.
• Automate security compliance, vulnerability remediation, and operational workflows.
• Support containerized and Kubernetes-based automation platforms.

Collaboration & Leadership

• Provide technical leadership and mentorship to automation and engineering teams.
• Conduct architecture reviews, code reviews, and technical assessments.
• Engage with clients and stakeholders to gather requirements and recommend AI automation strategies.
• Participate in solution workshops, proofs of concept, and innovation initiatives.

Soft Skills

• Strong analytical and problem-solving…