Machine Learning Threat Intelligence Engineer

Role

Seeking a Technical AI Solution Engineer / Machine Learning Threat Intelligence Engineer to design, architect, develop, and deliver AI and Generative AI solutions. The role focuses on rapidly building PoCs/MVPs, leading full solution lifecycles, and integrating LLM-based systems with enterprise environments.

Location & Contract

• Hybrid: Dallas, TX or Atlanta, GA
• Contract: 3–6 months
• Expected time commitment: ~3 to 6 hours per day

Key Responsibilities

• Lead end-to-end design of AI and GenAI solutions, including system architecture, data flows, model selection, and integration patterns.
• Partner with customers, product managers, and business teams to identify high-impact AI use cases.
• Evaluate AI technologies, frameworks, and vendors and recommend solution approaches.
• Build PoCs, MVPs, and production-grade features using vibe coding, LLMs, embeddings, retrieval, agents, and AI pipelines.
• Implement AI workflows such as MCP, RAG, fine-tuning, prompt engineering, agentic orchestration, and model optimization.
• Develop integrations with enterprise systems, APIs, data platforms, and cloud environments (AWS, Azure, Google Cloud Platform).
• Act as a subject-matter expert and advisor on modern AI/LLM architectures and infrastructure.
• Optionally conduct knowledge-sharing sessions, demos, and workshops with clients and internal teams.

Required Skills & Experience

• Strong hands-on experience with LLMs and GenAI frameworks (e.g., OpenAI, Azure OpenAI, Anthropic, Meta Llama).
• Experience building AI pipelines using MCP/RAG architectures, agents/multi-agent orchestration, prompt engineering, and fine-tuning or parameter-efficient training (LoRA, adapters).
• Proficiency in vibe coding and AI code generation tools.
• Proficiency in Python and/or Node.js, and experience with LangChain, Semantic Kernel, or LlamaIndex.
• Familiarity with ML frameworks such as PyTorch (TensorFlow optional).
• Experience with vector databases (Pinecone, Weaviate, Chroma, Redis Vector).
• Knowledge of cloud AI services: Azure, AWS, Google Cloud Platform.
• Strong understanding of API architectures, microservices, DevOps, CI/CD, and containerization.
• Experience translating business requirements into scalable AI solutions and interacting with customers.
• 5–10+ years in software or solution engineering; 2–3+ years in AI/ML or GenAI implementation.
• Bachelor’s or Master’s in Computer Science, Engineering, AI/ML, or a related field.

Preferred Qualifications

• Experience in telco, media, or large enterprise environments.
• Knowledge of data engineering, ETL pipelines, and feature stores.
• Experience with MLOps/LLMOps methodologies and tools.
• Exposure to vector search optimization, knowledge graphs, or reinforcement learning.
• Familiarity with responsible AI, security, governance, and compliance frameworks.

What We Offer

• Opportunity to build impactful AI solutions at scale in a collaborative environment.

Contact

For applications and inquiries: [email protected]