Senior AI Software Engineer (Agentic AI)

Description

Title:Senior AI Software Engineer (Agentic AI)

Location: San Francisco, CA

Duration: 3 months

Work Engagement: W2

Work Schedule: Hybrid 3 days in office/2 days remote

Compensation: $110-$128/hr is the pay range that the employer reasonably expects to pay for this position

Benefits on offer for this contract position: Health Insurance, Life insurance, 401K and Voluntary Benefits

Summary:

In this contingent resource assignment, you may: Consult on complex initiatives with broad impact and large-scale planning for Specialty Software Engineering. Review and analyze complex multi-faceted, larger scale, or longer-term Specialty Software Engineering challenges that require in-depth evaluation of multiple factors, including intangibles or unprecedented factors. Contribute to the resolution of complex and multi-faceted situations requiring solid understanding of the function, policies, procedures, and compliance requirements that meet deliverables. Strategically collaborate and consult with client personnel. Required Qualifications: Specialty Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education.

Key Responsibilities:

1. Build and Enhance AI Agents

• Develop, deploy, and maintain Agentic AI solutions.

• Create AI agents that automate and orchestrate marketing campaign activities.

• Support the scaling of the platform from the current agents to a larger enterprise ecosystem.

2. Develop Backend Services in Python

• Design and build Python-based backend applications and microservices.

• Write high-quality, production-ready, scalable code.

• Implement asynchronous and distributed processing solutions.

3. Design and Integrate APIs

• Develop REST APIs and service integrations.

• Enable communication between AI agents and enterprise systems.

• Support API performance, reliability, and security.

4. Implement LLM and Generative AI Solutions

• Build applications powered by Large Language Models (LLMs).

• Develop Agentic AI workflows and multi-agent systems.

• Create and optimize prompts, tool-calling, and model orchestration strategies.

5. Develop RAG and Knowledge Retrieval Systems

• Build Retrieval-Augmented Generation (RAG) solutions.

• Implement semantic search using embeddings and vector databases.

• Design hybrid and knowledge graph-enhanced retrieval architectures.

6. Optimize Performance and Scalability

• Improve application performance through profiling and tuning.

• Implement caching and database optimization strategies.

• Design highly available and fault-tolerant systems.

7. Manage Data and Database Solutions

• Work with MongoDB and vector databases.

• Design efficient data retrieval and storage patterns.

• Support embedding pipelines and semantic retrieval capabilities.

8. Apply AI Governance and Responsible AI Practices

• Implement AI guardrails and monitoring solutions.

• Support audit logging, model usage tracking, and compliance requirements.

• Help reduce hallucinations and improve AI response quality.

• Implement controls such as PII redaction and human-in-the-loop validation.

9. Collaborate with Engineering Teams

• Participate in daily standups and technical discussions.

• Work closely with developers and architects on solution design.

• Communicate technical blockers, risks, and dependencies.

• Provide support for production AI systems.

10. Continuously Improve AI Solutions

• Evaluate model performance and accuracy.

• Optimize latency, cost, and user experience.

• Contribute to feedback loops that improve AI agent effectiveness over time.

Key Requirements:

• Applicants must be authorized to work for ANY employer in the U.S. This position is not eligible for visa sponsorship.

• Python: 5+ years

• Microservices: 5+ years

• API Development/Integration: 5+ years

• MongoDB: 5+ years

• Agentic AI: 2+ years preferred