1 day ago
Pune, IndiaStaff+
Responsibilities
- Architect and deliver enterprise-grade AI solutions using Generative AI, large language models, agentic frameworks, AI copilots, domain-specific assistants, and multi-agent workflows.
- Design orchestration, reviewer, evaluator, and execution agents with human-in-the-loop controls, safety mechanisms, monitoring, and responsible AI practices.
- Build LLM-powered applications and RAG solutions using commercial and open-source models, semantic and hybrid search, embeddings, vector databases, enterprise knowledge bases, reranking, and retrieval optimization.
- Establish LLMOps capabilities for prompt lifecycle management, model evaluation, observability, performance and cost monitoring, testing, validation, and responsible AI controls.
- Lead development of React and TypeScript front ends and Python- or Java-based back-end services, APIs, microservices, and event-driven distributed systems.
- Build data and analytics solutions using BigQuery and PostgreSQL and apply machine learning to classification, ranking, recommendation, forecasting, feature engineering, and explainability.
- Define technical strategy, architecture, reusable engineering patterns, delivery standards, and working practices for AI-powered products and platforms.
- Guide prototypes from proof of concept through enterprise deployment while managing dependencies, trade-offs, quality, risk, maintainability, and scalability.
- Partner with product managers, business stakeholders, use case owners, and control functions to deliver measurable business and user outcomes.
- Mentor engineers, strengthen engineering standards, communicate complex technical concepts, and foster an inclusive culture of learning and experimentation.
Requirements
- Extensive hands-on software engineering experience designing and delivering enterprise-scale distributed applications and production-grade AI or Generative AI solutions.
- Deep expertise in ReactJS and TypeScript plus strong Python or Java engineering skills and practical experience with APIs, microservices, asynchronous applications, FastAPI, Spring Boot, or comparable frameworks.
- Strong experience with BigQuery, PostgreSQL, cloud-native architectures, Git-based development, CI/CD, Docker, Kubernetes, infrastructure as code, observability, automated testing, GitHub or Azure DevOps, Terraform, and OpenTelemetry.
- Practical expertise in LLM applications, AI agents, RAG architectures, vector databases, semantic or hybrid search, model evaluation, LLMOps, and relevant orchestration, evaluation, and observability tools.
- Solid grounding in machine learning, feature engineering, model explainability, analytical modeling, and Python machine learning libraries.
- Strong understanding of financial markets and investment products is highly desirable, including asset management, ETFs or mutual funds, and investment performance and risk metrics such as Sharpe Ratio, Information Ratio, Sortino Ratio, Alpha, Beta, and Tracking Error.
- Demonstrated technical leadership, including setting direction, leading by example, mentoring engineers, driving accountability, and fostering engineering excellence.
- Excellent stakeholder management, communication, collaboration, judgment, problem-solving, and ability to structure ambiguity and make pragmatic technical decisions.
- Bachelor’s degree in Computer Science, Engineering, Science, or a related discipline, or equivalent professional experience.
Tech Stack
DockerFastAPIGitGoogle BigQueryJavaKubernetesMLflowPostgreSQLPythonPyTorchReactscikit-learnSpring BootTerraformTypeScript
Categories
About DWS Group
DWS Group is a global asset manager that provides active, passive (Xtrackers ETFs), and alternative investment products for institutions, financial intermediaries, and individual investors. It earns management and performance fees across mutual funds and bespoke mandates, managing over €1 trillion in assets. Founded in 1956 and headquartered in Frankfurt, DWS is publicly listed in Germany and remains majority-owned by Deutsche Bank.