Boston, MA onsite 3 days/week
F2F interview mandatory
Full stack with Python and React on a AWS platform.
Need someone who has created agents in the last 6-12 months with Generatice AI/ Agentic AI
POSITION SUMMARY: This role is for a full-stack software engineer with specialization in AI to take holistic ownership of an enterprise-scale, strategic Data and AI platform. You ll be the primary engineer responsible for the mid-tier / business services layer of the bank s Enterprise Data & AI Platform, architecting and implementing the business solutions, workflows, API Integrations, services, and user-facing portals that connect business users to data, AI capabilities, and integrated third-party systems.
You ll build secure, scalable services and AI-based solutions using Python and other modern programming languages on Cloud platforms (AWS & Sowflake), ship production-grade UI experiences in React, and implement robust CI/CD and operational tooling on AWS Cloud stack. You will scan the horizon for the latest, greatest emerging tech in the AI domain, assess for maturity, and enable appropriate use and implementation in the bank.
You ll partner closely with Business, data engineering, security, and platform teams to ensure solutions are compliant, reliable, and easy to adopt across the bank.
While this role is extremely hands-on requiring advanced coding and programming skills, the ideal candidate will also possess architecture and design skills, provide thought leadership, and be a fast learner to swiftly scale and own new technologies and skill sets as needed.
RESPONSIBILITIES: List and describe this position s principal responsibilities in concise, comprehensive statements.
A. Platform & Service Ownership (Mid-Tier / Business Tier)
Own the design and delivery of the platform s application and integration layer: microservices/APIs, orchestration services, workflow backends, and shared business services.
Build and maintain the services that power AI solutions (e.g., RAG/chat experiences, workflow automations, document intelligence pipelines, decision support).
Define service boundaries, contracts, versioning, error handling standards, and performance SLAs for downstream consumers.
Implement platform golden paths for service creation (templates, libraries, deployment patterns, observability defaults).
A. Full-Stack Development (React + Python)
Build modern portals and internal tools in React for business users and admins (feature enablement, workflow configuration, analytics/telemetry views, content/knowledge management).
Develop backend services in Python (FastAPI/Flask preferred) supporting REST/GraphQL endpoints and async processing patterns as needed.
Integrate front end and back end with strong UX considerations, clear workflows, and robust validation.
A. AWS Cloud Engineering (Containers, Compute, Networking)
Deploy and operate workloads on AWS using EC2/ECS (and/or EKS), containerization (Docker), and cloud-native patterns.
Design for security and resiliency: VPC networking, private connectivity patterns where required, encryption, secrets management, and least-privilege access.
Implement scalable patterns (queues/events, background workers, caching) when workloads require it.
A. Integrations & APIs (Internal + Third-Party)
Design and implement integrations with internal systems and external vendors via APIs (REST/SOAP where applicable), including retries, idempotency, rate limiting, and circuit-breaker patterns.
Build a consistent integration framework for onboarding new services quickly while maintaining governance and observability.
Work with SMEs to translate integration needs into stable contracts and maintainable implementations.
A. Authentication, Authorization & Security-by-Design
Implement secure AuthN/AuthZ patterns (SSO, OAuth2/OIDC, SAML where needed), RBAC/ABAC, service-to-service auth, and token management.
Build enforcement points for data access controls, audit logging, and policy checks.
Partner with InfoSec, Risk, and Compliance to ensure the platform meets bank-grade expectations.
A. Data Warehouse & Analytics Enablement
Build service and UI patterns that sit cleanly on top of the bank s data warehouse (e.g., Snowflake/Redshift/Databricks depending on stack), including secure query services, metadata access, and governed data consumption.
Support data-driven features: usage telemetry, feature adoption metrics, workflow outcomes, and platform health dashboards.
Collaborate with data engineering to ensure the application tier uses data models efficiently and responsibly.
A. CI/CD, Reliability & Operations
Own CI/CD pipelines (GitHub Actions/Jenkins/CodePipeline), automated testing, quality gates, and repeatable release processes.
Implement production readiness standards: logging, monitoring, tracing, alerting, runbooks, on-call readiness (if applicable), and incident learnings.
Establish performance and cost hygiene (right-sizing, scaling policies, caching, and efficient service design)
KNOWLEDGE, SKILLS AND ABILITIES: Indicate the educational level, previous experience, specific knowledge, skills, and abilities required to meet the minimum entry-level requirements for this position. This may include special skills, licenses, certificates, etc.
- 12+ years of software engineering experience with demonstrated ownership of production systems
- Proven hands-on experience on AI technologies including GenAI models & services (AWS Bedrock, Snowflake Cortex etc.), frameworks (LangGraph, LangChain), Agentic AI, RAG etc.
- Strong backend engineering in Python (building APIs/services, async patterns, testing, packaging), and associated frameworks like FastAPI
- Strong front-end engineering in React (modern component design, state management, API integration).
- Hands-on AWS experience with Containers and AWS services including EC2, ECS, EKS, Amplify, API Gateway, Fargate, WAF, Load Balancer, etc.
- Experience building portals from scratch with backend integrations to multiple internal/external services via APIs.
- Strong understanding of AuthN/AuthZ (SSO, OAuth2/OIDC and/or SAML), RBAC, secrets management, and secure coding practices.
- Implementing CI/CD using AWS stack (Code Pipeline, CodeCommit, CodeCatalyst etc.) and comfortable operating systems in Production (debugging, monitoring, incident response basics).
- Familiarity with data warehouse concepts and patterns (governed access, query optimization, role-based controls)
Preferred Experience
- Familiarity with data warehouse concepts and patterns (governed access, query optimization, role-based controls)
- Past experience in Financial services industry is a strong plus
Education
- Bachelor s degree in Computer Science, Engineering, Information Systems, or related field (or equivalent experience).
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