AI-Driven OSINT Analyst

Role

Technical AI Solution Engineer responsible for designing, architecting, developing, and delivering AI and Generative AI solutions across customer use cases. The role combines solution architecture, hands-on development of PoCs/MVPs, and end-to-end delivery from ideation to production.

Location & Duration

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

Key Responsibilities

• Lead end-to-end AI and GenAI solution architecture, including system design, data flows, model selection, and integration patterns.
• Partner with customers, product managers, and business teams to identify high-impact AI use cases and translate business needs into technical designs.
• Rapidly build proofs of concept (PoC) and MVPs using LLMs, embeddings, retrieval, agents, and advanced AI pipelines.
• Implement AI workflows such as MCP, RAG, fine-tuning (LoRA/adapters), prompt engineering, and agentic orchestration.
• Integrate solutions with enterprise systems, APIs, data platforms, and cloud environments (Azure/AWS/GCP).
• Serve as a subject-matter expert and advisor on modern AI/LLM architectures, vector databases, and agentic automation.
• Conduct demos, workshops, and knowledge-sharing sessions as needed.

Required Skills & Experience

• Strong hands-on experience with LLMs and GenAI frameworks (OpenAI, Azure OpenAI, Anthropic, Meta Llama, etc.).
• Experience implementing MCP/RAG architectures, multi-agent orchestration, prompt engineering, and fine-tuning techniques.
• Proficiency with 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 (PyTorch, TensorFlow optional).
• Experience with vector databases (Pinecone, Weaviate, Chroma, Redis Vector).
• Knowledge of cloud AI services (Azure, AWS, Google Cloud Platform) and experience with API architectures, microservices, DevOps, CI/CD, and containerization.
• Strong communication, documentation, and solution delivery skills; experience interacting with customers and presenting technical solutions.

Preferred Qualifications

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

What We Offer

• Opportunity to build impactful AI solutions at scale and participate in next-generation AI innovation.
• Collaborative and supportive working environment.