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Salary
$29k – $75k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Senior · 6+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
State Street is an American financial institution founded in Boston in 1792 and one of the oldest banks in the United States, though its modern business bears little resemblance to retail banking. It is one of the three dominant global custodians, holding trillions of dollars of assets in safekeeping for institutional investors and providing the fund accounting, administration and settlement infrastructure that asset managers depend on. Its investment arm State Street Global Advisors created the first American exchange traded fund with the SPDR S&P 500 Trust and remains one of the largest index managers in the world.

Job Description: AI Enablement/Orchestration Engineer

Role Summary & Role Description

Our technology function, Global Technology Services (GTS), is vital to State Street and is the key enabler for our business to deliver data and insights to our clients. We’re driving the company’s digital transformation and expanding business capabilities using industry best practices and advanced technologies such as cloud, artificial intelligence and robotics process automation.

We offer a collaborative environment where technology skills and innovation are valued in a global organization. We’re looking for top technical talent to join our team and deliver creative technology solutions that help us become an end-to-end, next-generation financial services company.

Join us if you want to grow your technical skills, solve real problems and make your mark on our industry.

We are seeking a motivated and enthusiastic AI Enablement Engineer to join our team and contribute to the development and integration of cutting-edge AI solutions into our business processes. This is a highly technical and hands-on role where you will work closely with senior team members to build AI systems leveraging technologies such as Generative AI (Gen AI), Retrieval-Augmented Generation (RAG), Agentic AI frameworks. You will collaborate closely with software engineers and investment servicing business teams to solve complex business challenges in the payments domain.

This role requires strong capabilities in both AI Engineering and Data Engineering. You will design data products, orchestrate multi-agent workflows, develop Retrieval-Augmented Generation (RAG) systems, integrate enterprise knowledge sources, and establish the governance and observability capabilities required to operate AI safely within a highly regulated financial services environment.

State Street is accelerating the adoption of AI-enabled capabilities to improve operational efficiency, enhance cybersecurity resilience, strengthen risk management, and deliver intelligent experiences across the enterprise.

As an AI Orchestration Engineer, you will help establish the AI execution layer that enables secure collaboration between enterprise data platforms, large language models, internal knowledge repositories, agentic workflows, governance controls, and human decision makers.

What You Will Be Responsible For

  • Design, build, and operationalize AI/ML solutions to detect anomalies, exceptions, fraud indicators, operational risk signals, and process deviations across high-volume payment flows.
  • Develop anomaly detection models using supervised, unsupervised, semi-supervised, time-series, graph-based, statistical, and hybrid machine learning approaches.
  • Engineer features from payment transactions, exception events, operational logs, historical patterns, and reference data to identify unusual value, volume, velocity, counterparty, timing, currency, geography, and repair/reject behaviors.
  • Build scalable batch, streaming, and near-real-time data pipelines to support payment monitoring, detection, scoring, alert generation, and downstream investigation workflows.
  • Tune detection thresholds, scoring logic, and model sensitivity to balance early detection, precision, recall, false positive reduction, and operational usability.
  • Develop explainability capabilities, reason codes, model diagnostics, and investigation summaries to help payment operations, risk, and technology teams understand why anomalies are flagged.
  • Integrate anomaly detection services with payment applications, case management tools, workflow platforms, APIs, data stores, and human-in-the-loop review processes.
  • Use GenAI, RAG, and agentic AI capabilities selectively to support alert summarization, root-cause analysis, knowledge retrieval, operational playbooks, and assisted triage.
  • Implement MLOps practices for experiment tracking, model versioning, deployment automation, reproducibility, monitoring, rollback, and production support.
  • Monitor model performance, alert quality, drift, data quality, investigation outcomes, SLA adherence, and production reliability across anomaly detection use cases.
  • Partner with payments operations, product, risk, compliance, architecture, cybersecurity, and engineering teams to translate business scenarios into detection patterns and AI-enabled controls.
  • Apply Responsible AI, model risk management, auditability, data governance, security, and regulatory control requirements for AI solutions in a financial services environment.
  • Collaborate with cross-functional teams to identify AI use cases and translate business requirements into agent-based solutions.

Education & Qualifications

Skills Required

  • Hands-on experience building anomaly detection, fraud detection, transaction monitoring, risk scoring, or payment intelligence models using supervised, unsupervised, semi-supervised, and hybrid approaches.
  • Strong understanding of anomaly detection techniques such as clustering, isolation forests, one-class SVM, autoencoders, gradient boosting, time-series anomaly detection, graph-based detection, and statistical outlier methods.
  • Ability to engineer features from high-volume payment data, including amount, currency, value date, settlement date, counterparty, account, geography, payment type, frequency, velocity, historical behavior, exception codes, and repair/reject patterns.
  • Experience tuning detection thresholds and model sensitivity to optimize precision, recall, F1 score, alert quality, false positive reduction, and operational triage effectiveness.
  • Knowledge of payment flows, payment exceptions, duplicate payments, unusual value or volume patterns, payment repairs, rejects, sanctions referrals, cut-off breaches, and operational risk indicators.
  • Experience deploying batch, streaming, or near-real-time inference pipelines using technologies such as Kafka, Spark, Airflow, cloud data platforms, APIs, and MLOps tooling.
  • Ability to implement explainability and investigation support using SHAP, LIME, reason codes, model diagnostics, rule-model hybrids, and GenAI-assisted alert summarization.
  • Experience monitoring model drift, data quality, alert trends, investigation outcomes, SLA performance, and production reliability for anomaly detection systems.

Minimum Qualifications

  • 6+ years of professional experience; Bachelor's or Master's in Computer Science, AI/ML or related field.
  • 3-5 years of experience in Data Engineering, AI Engineering, Machine Learning Engineering, Software Engineering, or related disciplines.
  • Strong experience developing large-scale data pipelines and distributed data-processing solutions.
  • Proficiency in Python with solid software engineering fundamentals
  • Experience with SQL, APIs, workflow automation, and cloud-native architectures.
  • Solid understanding of RAG, experience with OpenAI Service and prompt engineering techniques. Knowledge of vector databases.
  • Experience integrating LLMs with external databases, APIs and storage systems
  • Experience in CI/CD-based projects. Knowledge of Docker and Kubernetes for deploying AI services
  • Strong communication and stakeholder collaboration skills.
  • Experience using Jira as an agile management tool.

Preferred Qualifications

  • Experience in Payments domain. Familiarity with payment standards and rails such as SWIFT, ISO 20022, wires, ACH, SEPA, real-time payments, and cross-border payment processing is preferred.
  • Experience in IBM MQ, Kafka, MFT.
  • Knowledge of Responsible AI, data governance, and model risk management.

Work Schedule

Hybrid

Keywords (If any)

Why this role is important to us

Our technology function, Global Technology Services (GTS), is vital to State Street and is the key enabler for our business to deliver data and insights to our clients. We’re driving the company’s digital transformation and expanding business capabilities using industry best practices and advanced technologies such as cloud, artificial intelligence and robotics process automation.

We offer a collaborative environment where technology skills and innovation are valued in a global organization. We’re looking for top technical talent to join our team and deliver creative technology solutions that help us become an end-to-end, next-generation financial services company.

Join us if you want to grow your technical skills, solve real problems and make your mark on our industry.

About State Street

What we do. State Street is one of the largest custodian banks, asset managers and asset intelligence companies in the world. From technology to product innovation, we’re making our mark on the financial services industry. For more than two centuries, we’ve been helping our clients safeguard and steward the investments of millions of people. We provide investment servicing, data & analytics, investment research & trading and investment management to institutional clients.

Work, Live and Grow. We make all efforts to create a great work environment. Our benefits packages are competitive and comprehensive. Details vary by location, but you may expect generous medical care, insurance and savings plans, among other perks. You’ll have access to flexible Work Programs to help you match your needs. And our wealth of development programs and educational support will help you reach your full potential.

Inclusion, Diversity and Social Responsibility. We truly believe our employees’ diverse backgrounds, experiences and perspectives are a powerful contributor to creating an inclusive environment where everyone can thrive and reach their maximum potential while adding value to both our organization and our clients. We warmly welcome candidates of diverse origin, background, ability, age, sexual orientation, gender identity and personality. Another fundamental value at State Street is active engagement with our communities around the world, both as a partner and a leader. You will have tools to help balance your professional and personal life, paid volunteer days, matching gift programs and access to employee networks that help you stay connected to what matters to you.

State Street is an equal opportunity and affirmative action employer.

Discover more at StateStreet.com/careers

About State Street

Across the globe, institutional investors rely on us to help them manage risk, respond to challenges, and drive performance and profitability. We keep our clients at the heart of everything we do, and smart, engaged employees are essential to our continued success.

We are committed to fostering an environment where every employee feels valued and empowered to reach their full potential. As an essential partner in our shared success, you’ll benefit from inclusive development opportunities, flexible work-life support, paid volunteer days, and vibrant employee networks that keep you connected to what matters most. Join us in shaping the future.

As an Equal Opportunity Employer, we consider all qualified applicants for all positions without regard to race, creed, color, religion, national origin, ancestry, ethnicity, age, disability, genetic information, sex, sexual orientation, gender identity or expression, citizenship, marital status, domestic partnership or civil union status, familial status, military and veteran status, and other characteristics protected by applicable law.

Discover more information on jobs at StateStreet.com/careers

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