Executive Director Principal Software Engineer - Agentic Engineering

Next Frontier Capital; Jersey City (NJ); On-site; USD 180,000 - 250,000; Full time

Benefits offered by this job

Health care coverage

On-site health and wellness centers

Retirement savings plan

Tuition reimbursement

Mental health support

Financial coaching

Job summary

JPMorgan Chase & Co. in Jersey City seeks a Principal Software Engineer to lead the design, build, and scaling of a next‑generation multi‑agent AI platform. You will write production code, own key architectural decisions, unblock engineers, and drive production outcomes while shaping strategy and building a high‑performing team.

If you have built agentic systems in production and can articulate orchestration vs. parallelization in distributed environments, this role is for you.

Qualifications

• 10+ years in software engineering and 5+ years leading senior technical teams
• Expert Python; working proficiency in TypeScript, Go, or Rust
• Deep familiarity with agentic frameworks (LangChain, LangGraph, AutoGen)
• Strong command of RAG, prompt/context design, tool/function calling, and multi-step reasoning
• Distributed systems and data platform experience: Kafka, Spark, gRPC/REST, Docker/Kubernetes
• Cloud fluency (AWS/Azure/GCP) and MLOps tooling (MLflow, Kubeflow, SageMaker, Vertex AI)
• Familiarity with vector databases, knowledge graphs, and semantic retrieval patterns
• Strong executive communication to align stakeholders on trade-offs, timelines, and risk
• Platform mindset: builds durable systems, not fragile demos

Responsibilities

• Own the multi-year agentic platform strategy: agent toolchains, RAG pipelines, memory/state architectures, context management, evaluation, and feedback/reinforcement loops.
• Architect scalable multi-agent systems using LangChain, LangGraph, AutoGen, or equivalent frameworks—and define when to use simpler primitives.
• Design distributed ingestion and workflow systems (batch + streaming) with data contracts, lineage, and strong data-quality patterns.
• Establish standards for the agentic development lifecycle: context engineering, automated evals, observability, security, and release readiness.
• Contribute directly in Python (services, concurrency, performance, reliability) and set the bar via reference implementations.
• Lead design and code reviews; engage directly in incident response and production hardening.
• Build reusable agent components: planning/decomposition, tool/function calling, self-critique/reflection loops, state management, multi-agent coordination, and safety controls.
• Partner with MLOps/platform on deployment, monitoring, and retraining pipelines (MLflow, SageMaker, Vertex AI, Azure ML)

Skills

Python

TypeScript

Go

Rust

Agentic frameworks

RAG / prompt design

Distributed systems

MLOps

Cloud platforms

Tools

Kafka

Spark

Docker

Kubernetes

gRPC/REST

MLflow

SageMaker

Vertex AI

LangChain

Job description

If you are looking for a game-changing career, working for one of the world's leading financial institutions, you’ve come to the right place.

As the Principal Software Engineer at JPMorgan Chase within the Corporate and Investment Bank Technology – Securitized Product Group Technology team, you will lead the design, build, and scaling of our next‑generation multi‑agent AI platform. This is not a manage‑from‑a‑distance role: you will write production code, own key architectural decisions, unblock engineers, and be accountable for production outcomes—while also setting multi‑year strategy and building a high‑performing team.

If you’ve built agentic systems in production (not prototypes), can distinguish orchestration vs. parallelization in real distributed environments, and can whiteboard with a CTO then land a PR the same afternoon—this role is for you

Job responsibilities

• Own the multi‑year agentic platform strategy: agent toolchains, RAG pipelines, memory/state architectures, context management, evaluation, and feedback/reinforcement loops.
• Architect scalable multi‑agent systems using LangChain, LangGraph, AutoGen, or equivalent frameworks—and define when to use simpler primitives.
• Design distributed ingestion and workflow systems (batch + streaming) with data contracts, lineage, and strong data‑quality patterns.
• Establish standards for the agentic development lifecycle: context engineering, automated evals, observability, security, and release readiness.
• Contribute directly in Python (services, concurrency, performance, reliability) and set the bar via reference implementations.
• Lead design and code reviews; engage directly in incident response and production hardening.
• Build reusable agent components: planning/decomposition, tool/function calling, self‑critique/reflection loops, state management, multi‑agent coordination, and safety controls.
• Partner with MLOps/platform on deployment, monitoring, and retraining pipelines (MLflow, SageMaker, Vertex AI, Azure ML, etc.).

Required qualifications, capabilities, and skills

• 10+ years in software engineering, including 5+ years leading senior technical teams and driving architecture for large systems.
• Expert Python; working proficiency in TypeScript, Go, or Rust.
• Deep familiarity with agentic frameworks (LangChain, LangGraph, AutoGen, or equivalent).
• Strong command of RAG, prompt/context design, tool/function calling, and multi‑step reasoning patterns.
• Distributed systems and data platform experience: Kafka, Spark, gRPC/REST, Docker/Kubernetes.
• Cloud fluency (AWS/Azure/GCP) and MLOps tooling (MLflow, Kubeflow, SageMaker, Vertex AI).
• Familiarity with vector databases, knowledge graphs, and semantic retrieval patterns.
• Strong executive communication—able to align stakeholders on trade‑offs, timelines, and risk.
• Platform mindset: builds durable systems, not fragile demos.

Preferred qualifications, capabilities, and skills

• kdb+/q, ClickHouse, or other time‑series/analytical data stores.
• Financial services domain (trading infrastructure, derivatives, fixed income).
• Publications, talks, or open‑source contributions in agentic AI.
• Experience designing “agentic SDLC” / software‑delivery automation.

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission‑based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on‑site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans

J.P. Morgan’s Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world. Provide expertise and engineering excellence to enhance, build and deliver market‑leading technologies within the firm