Developer
- Agile (Scaled Agile Framework)
- Containers (Azure Kubernetes)
- CI/CD (Azure DevOps, Git, SonarQube)
- Scheduling Tools (Azure Scheduler)
- AI orchestration
- Python
- AI: Machine learning, deep learning, neural networks, NLP, LLM’s
- App: Microservices (Java, Spring boot)
- UI & Web (ReactJS, HTML, Javascript)
- Database (SQL Server, Cosmos DB)
- APIs (Kong, APIC, APIM)
- IDE (GitHub Copilot, VSCODE, IntelliJ)
- Cloud Platform (Microsoft Azure)
- Secure Coding (Veracode)
- Authentication/Authorization (CA SiteMinder, MS Entra, PingOne)
- Log & Monitoring (Azure AppInsights, Elastic, )
- Define and implement GenAI building standards to ensure consistency, quality, and scalability across projects
- Stay abreast of advancements in GenAI and agentic systems, translating emerging trends into actionable opportunities
- Hands-on engineer in technical design and development of AI applications using existing and/or emerging technology.
- Work closely with product managers, data scientists and other stakeholders to translate business requirements into scalable and efficient AI solutions.
- Collaborate with cross-functional teams to execute the AI technology roadmap, aligning with business objectives and industry trends.
- Stay abreast of the latest advancements in AI technologies, guiding the team in adopting best practices and cutting-edge methodologies.
- Responsible for development of AI specific software/platform components.
- Investigate and resolve production management incidents, problems, and service requests.
- Implementation of AI technology best practices, architecture and technology stack including adoption of cloud, Data, and other relevant emerging technology that is fit-for-purpose.
- Ways of Working – Adoption of the Agile ways of working in the softwar e delivery lifecycle and continuous learning of new methods and technology
- 5+ years in development using multiple technology stack capabilities (Front/Back End, API, Database Mgmt., Hosting technologies etc. to drive digital transformation in financial services or technology domain
- Proven expertise in developing and delivering GenAI applications, including agentic systems
- Strong understanding of modern AI/ML frameworks, cloud platforms (e.g., AWS, Azure, GCP), and data engineering practices.
- Experience with LLMs, transformers, and understanding of agentic systems, current limitations and opportunities.
- Experience in implementing Enterprise AI solutions leveraging AI\ML models.
- Expertise in machine learning, deep learning, natural language processing, and other AI-related technologies.
- Proficiency in programming languages such as Python and proficiency with AI frameworks (e.g., TensorFlow, PyTorch)
- Strong grounding on data engineering and design to support AI workloads.
- Hands on experience on Azure AI offerings will be an added advantage.
- Strong analytical and problem-solving skills with a focus on delivering practical, scalable solutions.
- Hands-on experience in developing and implementing applications using modern technology stack and patterns including cloud native patterns, public cloud (e.g. Microsoft Azure), AI/Big Data, API and web apps
- Proficiency in software development lifecycle including CI/CD, test driven development, domain driven design and Agile ways of working (including shift-left)
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