Solutions Engineering Manager Jobs in Delaware

INTRODUCTION

Note: Need 15+ Year exp, kindly dont apply junior profile with 6-8 yrs exp.

ROLE AND RESPONSIBILITIES

Architecture Ownership

- Own the end‑to‑end architecture for the AI‑agent, DSL, and SFMC automation ecosystem.
- Design agentic AI systems, backend microservices, APIs, and SFMC integrations (REST/SOAP).
- Define DSL schemas (JSON/YAML) for AI‑generated workflows, ensuring extensibility, safety, and deterministic execution.
- Establish guardrails, validation, simulation, and compliance frameworks for AI‑generated journeys and campaigns.
- Create and maintain system blueprints, including data flow diagrams, integration contracts, and deployment architecture.

Technical Leadership

- Act as the hands‑on technical lead, guiding AI/ML engineers, DSL engineers, backend developers, and SFMC specialists.
- Lead POCs, prototypes, and architectural spikes to validate design decisions and technology choices.
- Drive coding standards, design patterns, and best practices across engineering teams.
- Conduct architectural reviews, code reviews, and design walkthroughs.
- Unblock teams, make technical decisions, and ensure alignment with architectural vision.

AI/ML & Agentic Systems

- Partner with AI/ML teams on:
- Agent frameworks (Agent SDK, LangChain, LangGraph, CrewAI, Semantic Kernel)
- RAG pipelines, embeddings, and vectorization
- LLM fine‑tuning, evaluation, and safety mechanisms
- Define prompting strategies, context engineering, and model‑interaction patterns.

Backend, Cloud & Integration Architecture

- Architect cloud‑native, highly available systems on AWS using IaC (Terraform).
- Oversee backend microservices, orchestration layers, and execution pipelines.
- Ensure robust integration with SFMC components:
- Journey Builder
- Email Studio
- Data Extensions
- Personalization logic
- REST/SOAP APIs
- Ensure observability, monitoring, logging, and reliability across all services.

Security, Governance & Compliance

- Ensure compliance with security, privacy, and governance requirements for AI‑generated marketing workflows.
- Define architectural controls for safe execution, auditability, and data protection.
- Lead performance optimization, scalability planning, and risk mitigation.

Cross‑Functional Collaboration

- Work closely with business, product, CRM, and marketing operations teams to translate requirements into scalable technical solutions.
- Communicate architectural decisions clearly to both technical and non‑technical stakeholders.

BASIC QUALIFICATIONS

• 10+ years of software engineering experience with at least 3+ years in a Tech Lead or Architect role.
• Strong background in AI/ML systems, including:
• LLMs
• Agentic architectures
• Prompt engineering
• RAG pipelines
• Experience designing complex distributed systems and workflow automation platforms.
• Deep understanding of DSL design, interpreters, ASTs, and compiler concepts.
• Strong proficiency in Python, TypeScript, or Java.
• Experience with cloud‑native architectures (AWS/Azure/GCP), containers, and microservices.
• Proven ability to lead engineering teams, conduct design reviews, and drive technical decisions.
• Excellent communication and stakeholder management skills.

PREFERRED QUALIFICATIONS

• Experience building AI‑driven workflow automation or autonomous agent systems.
• Familiarity with AMPscript and SSJS.
• Background in marketing automation, CRM systems, or customer lifecycle design.
• Experience with security, compliance, and governance for AI systems.
• Prior experience in fixed‑bid or outcome‑based delivery environments.
• Experience with event‑driven architectures and messaging systems.