

Openkyber
AI-Driven OSINT Analyst
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AI-Driven OSINT Analyst in Dallas, TX or Atlanta, GA (Hybrid) for a 3-6 month contract, offering a pay rate of "unknown." Key skills include LLMs, GAI frameworks, Python/Node.js, and cloud services. A Bachelor's/Master's in Computer Science or related field is required.
🌎 - Country
United States
💱 - Currency
Unknown
-
💰 - Day rate
Unknown
-
🗓️ - Date
February 10, 2026
🕒 - Duration
3 to 6 months
-
🏝️ - Location
Remote
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
Georgia
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🧠 - Skills detailed
#Deployment #AI (Artificial Intelligence) #Redis #Automation #Compliance #Python #Documentation #AWS (Amazon Web Services) #Databases #Data Engineering #Knowledge Graph #"ETL (Extract #Transform #Load)" #PyTorch #Security #Model Optimization #TensorFlow #ML (Machine Learning) #Microservices #Langchain #Reinforcement Learning #API (Application Programming Interface) #Cloud #GCP (Google Cloud Platform) #Computer Science #Azure #DevOps #Scala
Role description
Position: Technical AI Solution Engineer Location: Dallas TX or Atlanta GA (Hybrid) Duration: 3-6 months contract Note: Expected time commitment (hours per week / total duration) 3 to 6 hours per day
Job Description: Seeking a highly skilled Technical AI Solution Engineer to design, architect, develop, and deliver cutting edge AI and Generative AI (GAI) solutions across our customer needs. This role combines deep technical expertise in modern AI technologies with strong solution engineering capabilities and hands on implementation skills. The ideal candidate can translate business challenges into scalable AI-driven solutions, rapidly build PoCs/MVPs, and lead the full solution lifecycle - from ideation to production deployment. Key Responsibilities:
AI Solution Architecture & Design Lead the end to end design of AI and Generative AI solutions, including system architecture, data flows, model selection, and integration patterns. Partner with customers, product managers, and business teams to identify high impact AI-driven use cases. Evaluate AI technologies, frameworks, and vendors to recommend optimal solution approaches.
Hands On Development & PoC/MVP Creation Build proofs of concept (PoC), MVPs, and production-grade features using Vibe coding, LLMs, embeddings, retrieval, agents, and advanced 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).
Technical Expertise & Evangelism Serve as a subject-matter expert and advisor on modern AI, GenAI, and LLM-based architectures. Stay up to date with advancements in AI infrastructure, LLM capabilities, vector databases, and agentic automation.
Nice to have: Ability to conduct knowledge-sharing sessions, demos, and workshops with clients and internal teams. Required Skills & Experience
Strong hands on experience with LLMs, GAI frameworks, and modern AI stacks (OpenAI, Azure OpenAI, Anthropic, Meta Llama, etc.)
Experience building AI pipelines using: MCP/RAG architectures, Agents / multi agent orchestration, Prompt engineering & evaluation techniques, Fine tuning or parameter-efficient training (LoRA, adapters, etc.)
Proficiency in Vibe coding using the latest AI Code generation tools
Proficiency in Python and/or Node.js, including: LangChain / Semantic Kernel / LlamaIndex
ML frameworks (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.
Solution Engineering & Delivery Skills
Proven ability to translate business needs into scalable AI designs.
Experience interacting with customers, gathering requirements, and presenting technical solutions.
Strong documentation, architecture diagramming, and communication skills.
Background 5 10+ years in software engineering or solution engineering. 2 3+ years specifically in AI/ML or GenAI implementation. Bachelor's/Master's in Computer Science, Engineering, AI/ML, or related fields.
Preferred Qualifications Experience with telco and media, or large enterprise environments. Knowledge of data engineering, ETL pipelines, feature stores. Experience with MLOps or 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 massive scale. A front-row seat in Amdocs' next-generation AI innovation. A collaborative, innovative, and supportive environment.
For applications and inquiries, contact: hirings@openkyber.com
Position: Technical AI Solution Engineer Location: Dallas TX or Atlanta GA (Hybrid) Duration: 3-6 months contract Note: Expected time commitment (hours per week / total duration) 3 to 6 hours per day
Job Description: Seeking a highly skilled Technical AI Solution Engineer to design, architect, develop, and deliver cutting edge AI and Generative AI (GAI) solutions across our customer needs. This role combines deep technical expertise in modern AI technologies with strong solution engineering capabilities and hands on implementation skills. The ideal candidate can translate business challenges into scalable AI-driven solutions, rapidly build PoCs/MVPs, and lead the full solution lifecycle - from ideation to production deployment. Key Responsibilities:
AI Solution Architecture & Design Lead the end to end design of AI and Generative AI solutions, including system architecture, data flows, model selection, and integration patterns. Partner with customers, product managers, and business teams to identify high impact AI-driven use cases. Evaluate AI technologies, frameworks, and vendors to recommend optimal solution approaches.
Hands On Development & PoC/MVP Creation Build proofs of concept (PoC), MVPs, and production-grade features using Vibe coding, LLMs, embeddings, retrieval, agents, and advanced 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).
Technical Expertise & Evangelism Serve as a subject-matter expert and advisor on modern AI, GenAI, and LLM-based architectures. Stay up to date with advancements in AI infrastructure, LLM capabilities, vector databases, and agentic automation.
Nice to have: Ability to conduct knowledge-sharing sessions, demos, and workshops with clients and internal teams. Required Skills & Experience
Strong hands on experience with LLMs, GAI frameworks, and modern AI stacks (OpenAI, Azure OpenAI, Anthropic, Meta Llama, etc.)
Experience building AI pipelines using: MCP/RAG architectures, Agents / multi agent orchestration, Prompt engineering & evaluation techniques, Fine tuning or parameter-efficient training (LoRA, adapters, etc.)
Proficiency in Vibe coding using the latest AI Code generation tools
Proficiency in Python and/or Node.js, including: LangChain / Semantic Kernel / LlamaIndex
ML frameworks (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.
Solution Engineering & Delivery Skills
Proven ability to translate business needs into scalable AI designs.
Experience interacting with customers, gathering requirements, and presenting technical solutions.
Strong documentation, architecture diagramming, and communication skills.
Background 5 10+ years in software engineering or solution engineering. 2 3+ years specifically in AI/ML or GenAI implementation. Bachelor's/Master's in Computer Science, Engineering, AI/ML, or related fields.
Preferred Qualifications Experience with telco and media, or large enterprise environments. Knowledge of data engineering, ETL pipelines, feature stores. Experience with MLOps or 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 massive scale. A front-row seat in Amdocs' next-generation AI innovation. A collaborative, innovative, and supportive environment.
For applications and inquiries, contact: hirings@openkyber.com




