Software Developer with full‑stack expertise in Python, R, FastAPI, and modern cloud architectures, responsible for designing, deploying, and maintaining complex software solutions in a regulatory environment.
Responsibilities
Owns tasks and topics in the grey zone, driving small to medium initiatives
Challenges status quo and fosters collaboration, knowledge sharing, coaching, and mentoring
Prioritizes and communicates with stakeholders effectively
Aligns development plans with global strategy and engages in knowledge‑sharing events
Operates at the product/site level and implements technical strategies aligned with organizational objectives
Requirements
Bachelor's degree in Computer Science, Software Engineering, or related technical field
Design, develop, and deliver modern, cloud-native applications and services within the RxIO program
Contribute across the full software development lifecycle, including solution design, implementation, automated testing, performance optimization, production readiness, troubleshooting, and continuous improvement
Collaborate with architects, product teams, engineering teams, and other RxIO domain teams to deliver secure, scalable, resilient, maintainable, and extensible solutions supporting the broader RxIO platform
Requirements
Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, Information Technology, or a related technical field, or equivalent practical/professional experience
Master's degree in Computer Science, Software Engineering, Computer Engineering, or a related technical discipline is preferred
Nice to have: Java 21
Nice to have: Spring Boot 3.x
Nice to have: Google Cloud Platform (GKE, Cloud Spanner, Cloud Storage, BigQuery, Dataflow, Cloud Composer)
Lead the design and implementation of production-grade AI agent systems, including backend services, orchestration, retrieval, evaluation, observability, and deployment.
Own the technical design and implementation of AI agent systems
Build robust backend services, APIs, adapters, and connectors
Design agent workflows involving tool use, routing, state management, memory, retrieval, human-in-the-loop steps, and controlled multi-step execution
Develop retrieval and knowledge-grounding capabilities, including RAG pipelines, SQL-based agents, web search, reranking, citation, and context management
Define and implement evaluation strategies using representative datasets, golden tests, failure taxonomies, regression testing, human review, and production feedback
Requirements
Master’s degree in Computer Science, Software Engineering, or a related technical field
Design and implement backend microservices and APIs within established architectural patterns, owning services end-to-end and mentoring junior engineers.
Responsibilities
Design and implement backend microservices and APIs
Take ownership of services: write code, own tests, ship to production
Work towards team engineering practices: code reviews, improve test coverage, flag gaps in pipeline and operational readiness
Mentor junior and associate engineers through code reviews, pair work, and direct feedback
Apply spec-driven development and AI-assisted tooling as a standard part of how you work
Lead mobile engineering for native iOS and Android applications within JPMorgan Chase’s Asset & Wealth Management International Private Bank Technology organization.
Responsibilities
Designs and develops secure, high-quality production code for native iOS and Android client applications, instrumenting them for crash reporting, performance monitoring, logging and telemetry; reviews, debugs and improves code written by others.
Drives design and implementation decisions for mobile observability capabilities—SLIs/SLOs, alerting thresholds, distributed tracing and real user monitoring—balancing data integrity, performance, security, reliability, maintainability and operating cost.
Provides technical guidance to engineering and business partners, acting as a subject matter expert in native mobile development and mobile application performance management (APM).
Leads the technical delivery of complex observability initiatives through implementation, testing, integration, controlled migration, release readiness and operational support, including triage and root‑cause analysis of production incidents using crash and performance telemetry.
Applies enterprise‑authorised coding agents and automation across design, implementation, testing, review and troubleshooting for iOS and Android codebases, creating reusable context, tools and workflows.
Requirements
Bachelor's or equivalent in Computer Science, Computer Engineering, Mathematics, or a related technical field
Forward Deployed Engineer combines hands‑on software engineering with client‑facing delivery, turning business requirements into production‑ready AI solutions.
Responsibilities
Work embedded with client and Sia teams, taking part in planning, stand‑ups, and delivery activities.
Run technical discovery with client stakeholders and turn business needs into scoped, buildable deliverables with clear acceptance criteria.
Build production‑grade Python services and APIs (FastAPI and REST) that power Generative AI applications, including RAG pipelines over enterprise knowledge sources.
Integrate LLM APIs and SDKs into client environments, handling authentication, rate limits, fallbacks, latency, and cost.
Connect solutions to enterprise systems such as databases, internal APIs, document stores, and business applications.
Requirements
Bachelor's or Master's degree in Computer Science, Engineering or a related field, or equivalent practical experience.
Nice to have: Agent orchestration and tool‑calling frameworks (LangGraph, LangChain, OpenAI or Claude SDKs)
Nice to have: Model Context Protocol (MCP)
Nice to have: Enterprise GenAI platforms and managed AI services on AWS Azure or GCP
The likely salary range for this position is $140,821 - $190,523.
Responsibilities
Implement Role-Based Access Controls (RBAC) and Attribute-Based Access Controls (ABAC) to restrict access and define permissions according to the user’s role, attributes, and need to know.
Incorporate observability best practices, including continuous tuning of alerts to reduce noise, data quality validation prior to ingestion, structured logging conventions, and adherence to security and governance policies.
Design contextualized, role specific insight dashboards that tailor visualizations to operator, analyst, and leadership mission workflows for improved decision making.
Conduct continuous capacity planning using telemetry trends, resource consumption analytics, forecasting models, and platform performance indicators.
Design and build backend services for an investment technology platform, including REST and GraphQL APIs, asynchronous workflows, and relational data models.
Responsibilities
Own backend features and services throughout their lifecycle
Design and develop REST and GraphQL APIs
Build reliable asynchronous workflows
Design relational data models and data access patterns
Build automated testing, structured logging, metrics and tracing
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