We are seeking a hands-on Financial Services Consultant with AI experience to design, build, and scale GenAI-powered solutions for banking and financial services. The role focuses on understanding business pain points, define solution leveraging AI techniques, with experience in LLM application development, agent orchestration, and data-driven AI pipelines to be developed for specific financial services use cases. Here are some AI engagements our consultants are working on: Improve Day in life of Wealth Advisor leveraging AI interventions such as – Client Profiling, Client Advisor Mapping, Meeting summarization, Next Best Action. Reduce false positives in Trade / AML Surveillance to ensure Compliance personnel are focusing their time on critical alerts. Faster onboarding of clients leveraging AI driven KYC processes – Negative News screening, Beneficial Ownership determination, Document information extraction and validation. Improve Operational processes leveraging AI / Gen AI – Corporate Actions, Reconciliations, Predict Settlement failures, etc Digitalization of Advisory Platforms covering end to end Advisory lifecycle from Prospecting to Portfolio Management Machine Learning driven personalization - life events, investment ideas, service alerts and assessment of client attrition risk Virtual Assistant - Cognitive Assistant Pilot (CAP) to guide Financial Advisors and Customer Support Associates in Salesforce. Comprehensive portal to do a “Best Match” and find a Financial Advisor (Individual or Teams) by name, nearby location, gender and International Wealth FAs and teams
Key Responsibilities:- Work with business stakeholders (Banking and financial services) to identify the problem statement and participate in / lead solution design. E.g. Understand Day in life of an Advisor, identify critical manual flows and define potential solutions
- Act as a Product Manager / Product Owner and work closely with architects, business SMEs, to develop business requirements and AI solutions
- Design and develop GenAI solutions using LLMs (Claude, OpenAI, etc.) to solve business problems such as Improving Advisor productivity, Operations efficiency in areas such as Corporate Actions, Portfolio Mgmt., AML / KYC processes.
- Build agent-based workflows using frameworks such as LangChain / Google ADK / similar
- Develop RAG pipelines, semantic search, and knowledge-driven applications
- Implement prompt engineering, evaluation frameworks, and guardrails
- Perform testing, validation, of final solution to ensure conformity to business problems and optimization of AI models and pipelines
- Coordinate with business and technology stakeholders for program delivery
Required Skills:- Experience in financial services industry (Capital markets / Banking) and familiarity with Front office / Middle office / Back office operations or processes
- Understanding of the end to end value chain (wealth management, asset management, investment banking, etc.)Experience with defining AI related KPIs and building AI adoption business case
- Experience in Python-based AI/ML development
- Understanding of:
- LLMs and GenAI architectures
- Prompt engineering and chaining techniques
- Data processing and pipelines
- Understanding of Graph RAG and hands-on with one or more:
- LangChain / similar frameworks
- Claude / OpenAI / other LLM APIsWorking knowledge of:
- Vector databases, embeddings, semantic searchAPI integrations and microservices
Basic Qualifications:- Bachelor’s degree or equivalent required
- Prior work experience of 8-12 years either in management consulting or directly working on advisory business, technology or operational change initiatives in Financial Services industry.
- Strong problem-solving mindset
- Ability to work in fast-paced AI delivery pods
- Ability to travel up to 75%.
Location:
Dallas, Charlotte, NJ/NYCandidates authorized to work for any employer in the United States without employer-based visa sponsorship are welcome to apply. Infosys is unable to provide immigration sponsorship for this role at this time. Preferred Qualifications / Skills Exposure to Google ADK / agentic frameworks Experience with knowledge graphs and graph-based retrieval Understanding of banking / financial services domain Familiarity with cloud platforms (Azure / AWS / GCP) Data engineering basics (SQL, schema, profiling) Ability and willingness to work as part of a cross-cultural team including flexibility to support multiple time zones when necessary Candidates should be able to ramp up quickly with minimal support, take full ownership of assigned tasks, and consistently deliver against timelines and commitments.
