Senior AI Engineer

Overview

The Senior AI Solutions Engineer identifies high-value AI use cases, assesses solution feasibility, prototypes innovative ideas, and delivers successful pilot projects. The role combines AI, software engineering, data engineering, cloud infrastructure, security, and enterprise integration expertise.

What you'll do

• Develop, fine-tune, and deploy AI models, including large language models such as GPT-4 or open-source equivalents.
• Design and implement prompt engineering strategies and optimizations to improve AI accuracy, consistency, and reliability.
• Engage with internal stakeholders and clients to understand business needs and translate them into actionable AI solutions.
• Rapidly prototype, test, and iterate AI applications using Python and relevant frameworks.
• Integrate AI solutions securely with enterprise systems through API development and integration.
• Build, maintain, and optimize end-to-end data pipelines for accurate and timely AI model data delivery.
• Manage structured and unstructured datasets using vector databases and semantic search.
• Deploy, manage, and scale AI solutions in Azure, AWS, or GCP cloud environments.
• Implement DevOps and MLOps practices, including automated deployment, testing, monitoring, and version control.
• Ensure AI solutions follow industry standards and compliance regulations including GDPR and HIPAA.
• Identify and mitigate AI deployment risks, including ethical considerations, biases, and unintended consequences.
• Collaborate with business and functional teams to streamline processes through intelligent automation and deliver measurable business outcomes.
• Document technical designs, project plans, and operational procedures.
• Contribute to AI best practices, methodologies, and internal frameworks.
• Evaluate emerging AI and machine learning technologies and methodologies.

What you'll need

• Advanced understanding of artificial intelligence, natural language processing, and machine learning principles.
• Advanced expertise selecting, fine-tuning, and deploying large and small language models, including OpenAI GPT series and open-source alternatives.
• Advanced proven experience with prompt engineering, prompt optimization, and AI model reliability and accuracy improvements.
• Advanced proficiency in Python programming.
• Advanced familiarity with full-stack software development, including frontend and backend integration, user experience considerations, and system interoperability.
• Robust knowledge of data pipeline development, data engineering concepts, and structured and unstructured data.
• Advanced proficiency in Azure, AWS, or GCP, particularly for deploying, scaling, and managing AI workloads.
• Advanced knowledge of security, compliance, and risk management practices related to AI solutions.
• Advanced understanding of ethical AI, bias mitigation, and responsible AI deployment.
• Demonstrated domain and business acumen to align technical solutions with business strategies and processes for measurable impact.
• Excellent communication skills and ability to explain technical concepts to non-technical stakeholders.
• Advanced analytical problem-solving capabilities, organizational skills, and attention to detail.
• Ability to manage multiple projects, prioritize tasks, and meet deadlines in a fast-paced environment.
• Passion for continuous learning, innovation, and industry trends.
• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field.
• Advanced demonstrated experience, typically 4-6 years, developing, deploying, and maintaining AI and machine learning solutions in enterprise environments.
• Advanced expertise in AI model development, fine-tuning, and optimization using Python and relevant frameworks.
• Advanced demonstrated experience implementing prompt engineering methodologies and optimizing model performance.
• Advanced demonstrated experience developing APIs and securely integrating AI-driven solutions with enterprise systems and platforms.
• Advanced experience building data pipelines, managing structured and unstructured data, and leveraging vector databases.
• Practical experience deploying and scaling AI applications within Azure, AWS, or GCP.
• Advanced demonstrated success applying DevOps and MLOps practices to AI model lifecycle management and deployments.
• Advanced proven track record ensuring security, privacy, compliance, and responsible use of AI solutions within regulated environments.
• Advanced experience engaging directly with clients and stakeholders and translating business requirements into technical solutions.

Nice to have

• Advanced knowledge of JavaScript or TypeScript for frontend interfaces or web integrations.
• Advanced knowledge of Java or C# for enterprise backend integrations such as ERP and CRM systems.
• Microsoft Certified: Azure AI Engineer Associate.
• Microsoft Certified: Azure Solutions Architect Expert.
• Microsoft Certified: Data Scientist Associate.
• Microsoft Certified: Azure Data Engineer Associate.
• Microsoft Certified: Power Platform Fundamentals.
• Relevant certifications or training in Machine Learning, AI development, Data Analytics, and Cloud Computing.

Details

• Location: Bangalore, India.
• Workplace type: Hybrid Working.