Job Title
Senior AI & Automation Engineer (Azure AI Platform)
Industry: Asset Management / Financial Services
Location: Offshore – India / Philippines
Experience: 5–8 Years
Role Overview
We are seeking a highly skilled Senior AI & Automation Engineer to design, build, and operationalise enterprise‑grade AI, machine learning, and automation solutions using Microsoft Azure AI and cloud platforms.
This role focuses on taking AI solutions from proof‑of‑concept to secure, scalable, and governed production deployments, enabling measurable business outcomes across investment, operations, and corporate functions.
The role requires strong hands‑on experience in LLMs, agentic AI, Azure AI platform services, RPA (Blue Prism), cloud‑native engineering, MLOps, and enterprise automation, with a strong emphasis on reliability, governance, and operational excellence.
Required Technical Skills (Mandatory)
AI & Machine Learning (Mandatory)
- Strong experience developing, deploying, and operating AI/ML models in production environments
- Hands‑on experience with Azure AI services (MANDATORY), including:
- Azure OpenAI
- Azure AI Search
- Azure Machine Learning
- Azure AI Studio / AI Foundry
- Hands‑on experience with Large Language Models (LLMs) and Agentic AI, including:
- Reasoning and planning
- Tool orchestration and function calling
- Memory management and multi‑step task execution
- Deep understanding of AI risks, including bias, hallucinations, explainability, and mitigation strategies
- Proven experience transitioning AI solutions from POC to enterprise‑scale production
Automation & RPA (Mandatory)
- Strong hands‑on experience in RPA using Blue Prism (MANDATORY)
- Proven experience designing, developing, and deploying enterprise‑grade automation solutions using Blue Prism
- Experience in intelligent process automation, integrating RPA with AI/ML models and APIs
- Experience building scalable automation frameworks, reusable components, and orchestrated workflows
- Strong understanding of process optimization, exception handling, and operational support for automation solutions
Software Engineering & Integration (Mandatory)
- Advanced proficiency in Python and at least one additional language (e.g., Java)
- Solid knowledge of API design principles, RESTful services, and system‑to‑system integration
- Experience integrating RPA, AI services, and enterprise platforms (e.g., ServiceNow, workflow systems)
- Experience designing and implementing microservices‑based architectures
- Strong understanding of distributed systems, messaging platforms, and event‑driven architectures
Cloud & Platform Engineering (Mandatory)
- Hands‑on experience with Microsoft Azure (MANDATORY), including AI/ML services and infrastructure
- Experience with containerisation (Docker) and orchestration (Kubernetes / AKS)
- Knowledge of SQL and NoSQL databases, data stores, and data engineering fundamentals
- Experience designing scalable, secure, and resilient cloud platforms aligned with enterprise standards
MLOps & DevOps (Mandatory)
- Strong experience with MLOps practices, including:
- Model versioning
- Monitoring and performance tracking
- Retraining strategies
- Deployment and rollback mechanisms
- Hands‑on experience with CI/CD pipelines, Git‑based workflows, and collaborative development practices
- Experience applying DevOps and platform engineering principles to AI and automation systems
Key Responsibilities
AI & Automation Delivery
- Design, develop, and deploy AI/ML and automation solutions to solve complex business problems
- Build and integrate LLM‑based, agentic AI, and RPA (Blue Prism) solutions
- Develop document, data, and workflow automation using AI, RPA, APIs, and event‑driven architectures
- Design and optimise large‑scale ML pipelines for training, evaluation, inference, and lifecycle management
Engineering & Architecture
- Design and implement scalable microservices‑based architectures for AI and automation platforms
- Build RESTful APIs and event‑driven services to embed AI and RPA capabilities into enterprise platforms (e.g., ServiceNow, workflow solutions, data platforms)
- Ensure high availability, fault tolerance, scalability, and performance optimisation of AI and automation systems
- Apply engineering best practices including testing, observability, logging, and monitoring
Operations, Quality & Governance
- Lead end‑to‑end operationalisation of AI and RPA solutions, including:
- Monitoring and alerting
- Incident management
- Retraining and release controls
- Implement CI/CD pipelines for automated testing, deployment, and release management
- Establish quality gates to prevent AI‑generated defects from reaching production
- Own and manage production AI and RPA environments with a focus on reliability, security, and operational excellence
- Define and enforce AI and automation governance frameworks, covering:
- Model risk management
- Ethics and responsible AI
- Transparency and explainability
- Regulatory and compliance requirements
Preferred Experience
- Experience working in regulated or enterprise environments
- Exposure to financial services, investment platforms, or large‑scale corporate systems
- Strong stakeholder engagement skills and experience working across business and technology teams
Qualifications
- Bachelor's Degree in IT / Engineering / Finance or related field
- Blue Prism Certification (Preferred)
