GDS Consulting_AI & Data_Senior AI Engineer

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Senior AI Engineer
Position Overview
We are seeking an experienced Senior AI Engineer to lead the design development and implementation of Agentic AI solutions. This role combines deep expertise in artificial intelligence process automation to create sophisticated agentic AI workflows that integrate seamlessly with enterprise tools and systems.
Key Responsibilities
AI and Automation Strategy
Design and architect end-to-end agentic ai solutions that combined with process automation
Lead the development of agentic AI workflows that can autonomously execute complex business processes
Evaluate and integrate cutting-edge AI technologies including large language models machine learning algorithms and cognitive automation tools
Establish best practices and standards for AI-driven automation implementations
Technical Development
Build and deploy agentic AI systems capable of multi-step reasoning planning and execution
Develop robust integrations between AI agents and enterprise tools (RPA CRM ERP databases APIs cloud services)
Create intelligent document processing solutions combining OCR NLP and computer vision technologies
Implement monitoring logging and error handling systems for automated workflows
Process Optimization
Analyze complex business processes to identify agentic ai automation opportunities
Collaborate with business stakeholders to understand requirements and translate them into technical solutions
Optimize existing automation workflows for performance reliability and scalability
Conduct process mining and analysis to identify bottlenecks and improvement opportunities
Leadership and Collaboration
Mentor junior engineers and provide technical guidance on AI and automation projects
Collaborate with cross-functional teams including data scientists software engineers and business analysts
Lead proof-of-concept initiatives and pilot programs for AI
Present technical solutions and recommendations to senior leadership and stakeholders
Required Qualifications*
Education and Experience
Bachelors degree in Computer science Engineering Data Science or related technical field
Minimum 5 years of experience in process automation and AI engineering
Minimum 3 years of hands-on experience with RPA platforms and tools
Minimum 2 years of experience building agentic AI workflows or autonomous AI systems
Technical Skills - Core Requirements
Advanced experience with AI/ML frameworks: TensorFlow PyTorch scikit-learn Hugging Face Transformers
Proven experience building agentic AI systems: Multi-agent frameworks (LangGraph Autogen N8N CrewAI) autonomous workflow orchestration AI planning and reasoning systems
Strong programming skills: Python (required) JavaScript C# Java or similar languages
API integration expertise: REST/SOAP APIs webhook implementation microservices architecture
Cloud platforms experience: AWS Azure or Google Cloud Platform with AI/ML services
Technical Skills - AI and Automation
Natural Language Processing: Experience with LLMs prompt engineering text analysis and conversational AI
Computer Vision: Image processing OCR technologies (Tesseract ABBYY Azure Cognitive Services)
Workflow orchestration: Apache Airflow Prefect or similar workflow management tools
Database technologies: SQL and NoSQL databases data pipeline development
DevOps and MLOps: CI/CD pipelines containerization (Docker Kubernetes) model deployment and monitoring
Integration and Tool Experience
Enterprise system integration: SAP Salesforce Microsoft Office 365 SharePoint Oracle applications
Business intelligence tools: Power BI Tableau or similar analytics platforms
Version control and collaboration: Git Azure DevOps Jira Confluence
Monitoring and logging: Application monitoring performance tracking error handling systems

Preferred Qualifications
Advanced Experience
Experience with multi-agent AI systems and agent-to-agent communication protocols
Background in cognitive automation and intelligent document processing (IDP)
Experience with process mining tools (Celonis ProcessGold Minit)
Knowledge of business process management (BPM) platforms
Certification in AI (Microsoft AI-102 UiPath AI Profesional)
Specialized Skills
Experience with reinforcement learning for process optimization
Knowledge of api integration in automation workflows
Background in cybersecurity and compliance automation
Experience with edge computing and IoT device automation
Familiarity with industry-specific automation (finance healthcare manufacturing)
Leadership and Communication
Experience leading technical teams and mentoring engineers
Track record of successful large-scale automation implementations
Strong presentation and communication skills for executive-level audiences
Experience with agile development methodologies and project management

Required Competencies
Technical Competencies
Systems thinking: Ability to design complex interconnected automation ecosystems
Problem-solving: Advanced analytical skills for troubleshooting and optimization
Innovative smindset: Stay current with emerging AI and automation technologies
Quality focus: Commitment to building robust scalable and maintainable solutions
Soft Skills
Communication: Ability to explain complex technical concepts to non-technical stakeholders
Collaboration: Work effectively with diverse teams across technical and business functions
Adaptability: Thrive in fast-paced environments with evolving technology landscapes
Leadership: Guide technical decisions and mentor team members

Performance Expectations
First 6 Months Objectives
Successfully design and implement at least 2 major agentic AI automation solutions
Mentor and upskill team members on advanced automation and AI technologies
Ongoing Responsibilities
Maintain 95% uptime for critical automation workflows
Continuously optimize existing solutions for performance and cost-effectiveness
Stay current with industry trends and recommend technology stack improvements
Contribute to the organizations AI and automation strategy and best practices

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