Senior Software Engineer (AI Solutions) in United States at Jobgether

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior Software Engineer (AI Solutions) in United States.

This role sits at the core of building next-generation AI-powered systems that transform how go-to-market teams understand and act on customer and revenue data. You will design and implement agentic AI workflows that turn fragmented signals—such as CRM records, call transcripts, and support interactions—into actionable insights and automated workflows. The position blends backend engineering, AI system design, and data integration, requiring a strong bias toward AI-native development practices. You will work closely with GTM stakeholders to continuously refine AI outputs and improve real-world business impact. Operating in a highly iterative environment, you will help shape architecture, optimize performance and cost, and ensure reliability across distributed AI systems. This is a hands-on role where you will actively build, experiment, and improve intelligent systems using modern AI tooling and agent frameworks. Your work will directly influence how sales, success, product, and marketing teams operate at scale.

• Design, build, and iterate on AI-powered workflows that transform GTM data (CRM, support, telemetry, communications) into structured insights and automated actions.
• Extend and maintain FastAPI- and LangGraph-based agent systems, including tool routing, prompt design, error handling, and observability.
• Integrate diverse data sources such as Zendesk, Salesforce, Google Drive, email, and telemetry pipelines into AWS-based architectures.
• Develop and optimize Lambda-based data processing workflows with a focus on performance, scalability, and cost efficiency.
• Define structured data models, JSON schemas, and pre-aggregated summaries for reliable AI-driven querying and retrieval.
• Collaborate with GTM teams (Sales, Customer Success, Product, Marketing) to design, test, and refine AI-driven workflows and insights.
• Evaluate and improve LLM performance through prompt engineering, routing strategies, and measurable quality metrics.
• Contribute to frontend features (React/TypeScript) and integration layers when needed to support end-to-end AI workflows.
• Help evolve agentic development practices, including multi-agent systems, evaluation pipelines, and emerging integration patterns.

• 3+ years of software engineering experience, including at least 1+ year building LLM-powered applications or agent-based systems.
• Strong proficiency in Python and backend development, ideally using FastAPI or similar asynchronous frameworks.
• Hands-on experience with LLM orchestration tools such as LangGraph, LangChain, or equivalent agent frameworks.
• Practical knowledge of retrieval-augmented generation (RAG), including chunking strategies, metadata design, and evaluation methods.
• Experience working with cloud environments (preferably AWS: Lambda, S3, Bedrock) and CI/CD pipelines.
• Familiarity with API and webhook integrations across SaaS tools such as Salesforce, Zendesk, Zoom, or Slack.
• Ability to design structured schemas, data models, and systems for reliable AI and data workflows.
• Working knowledge of modern frontend technologies such as React and TypeScript is a plus.
• Strong problem-solving mindset with comfort in ambiguity, experimentation, and fast iteration.
• Willingness to travel up to 20% for collaboration and stakeholder engagement.

• Competitive compensation package including a base salary aligned with experience and location tier ($165,000 – $249,000), plus equity and bonus eligibility.
• Opportunity to work at the forefront of AI-native software development and agentic systems.
• Equity participation in a high-growth organization focused on AI-driven innovation.
• Flexible work arrangements with remote-first collaboration.
• Comprehensive health, dental, and vision insurance coverage.
• Paid time off, holidays, and parental leave policies.
• 401(k) retirement savings plan and additional financial benefits.
• Access to modern AI tooling and an environment that encourages experimentation and continuous learning.