AI Solutions Engineer

AI Solutions Engineer

Qualifications

:

• Education: Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, or related field.

• Experience:

o 6+ years of experience in AI, machine learning, and solution architecture, with a proven track record of designing and deploying AI solutions.

o Hands-on experience with AI tools and platforms and cloud services like Microsoft Azure.

o Strong background in machine learning algorithms, deep learning, data processing, and systems integration. Ability to drive architecture governance, code quality, and technical standards.

o Proven experience delivering AI and digital transformation solutions within financial services, banking, fintech, regulatory authorities, or highly regulated environments, with a strong understanding of compliance, governance, risk management, and regulatory requirements.

• Technical Skills:

o Proficient in programming languages such as Python, Java, or C++.

o Familiarity with data pipeline tools and frameworks

o Experience with cloud infrastructure, containerization (Docker, Kubernetes), and DevOps practices.

o Solid understanding of data architecture, data science, security, and privacy considerations in AI systems.

o Design AI solutions integrated with enterprise platforms (Salesforce CRM, datalakes, CMS, APIs). Hands-on experience with frameworks like Hugging Face, LangChain, Foundry, OpenAI APIs etc.

o Demonstrated experience in designing, developing, and deploying Agentic AI solutions, including autonomous AI agents, multi-agent systems, AI orchestration frameworks, and agent-based workflow automation using platforms such as Azure AI Foundry, Agentforce, etc

• Soft Skills:

o Strong analytical and problem-solving skills.

o Ability to communicate complex technical concepts clearly to both technical and non-technical stakeholders.

o Leadership experience and the ability to work effectively in cross-functional teams.

o Detail-oriented and focused on delivering high-quality, scalable solutions.

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Data & Integration:

o  Familiarity with data engineering tools, data lakehouses (Fabric), and ETL pipelines.

o  Ability to integrate AI with enterprise platforms and legacy systems via RESTful APIs or middleware.

Preferred Qualifications:

• Experience with advanced AI techniques such as reinforcement learning, natural language processing, or computer vision.

• Knowledge of AI ethics and bias mitigation strategies.

Personal Attributes:

• Ability to innovate and think critically about solving complex business problems with AI.

• Strong interpersonal and communication skills for collaboration with stakeholders at all levels.

• Self-motivated, proactive, and comfortable working in a dynamic and fast-paced environment.