Lead the design, development, and deployment of cutting-edge AI solutions and agentic AI frameworks for the banking sector.
Compensation
$176,720.00 - $265,080.00
Responsibilities
Spearhead the end-to-end design, hands-on implementation, and deployment of scalable, robust agentic AI frameworks and generative AI solutions
Build full-stack applications that seamlessly integrate state-of-the-art ML/LLM tools and services into comprehensive AI solutions
Champion an MVP-first approach, focusing on rapid iterations, hypothesis testing, and A/B experiments
Design and implement rigorous metrics for AI system and performance
Proactively explore, prototype, and integrate the latest advancements in AI, particularly agent-based systems, autonomous AI, and generative technologies
The role focuses on advanced prompt engineering, foundation model optimization, and programmatic evaluation of LLM applications for financial services and healthcare sectors.
Responsibilities
Programmatically generate, test, and evaluate prompt performance at scale using Python.
Manage foundation model behaviors (GPT-4, Llama, Claude, Mistral), context window dynamics, and tokenization mechanics.
Implement output validation libraries (Pydantic, Instructor) and guardrail systems.
Focus on edge-case mapping, deterministic output formatting, and cost optimization.
Apply advanced prompting techniques such as Few-Shot Prompting, Chain-of-Thought (CoT), ReAct, and Context Engineering.
Lead the architecture, development, deployment, and ongoing evolution of AI initiatives across a global consumer SuperApp. This is a hands-on technical leadership role focused on open-source foundation models, self-hosted infrastructure, and production AI systems.
Compensation
Compensation is accrued and payable following funding, after which it transitions to a regular salary, equity ownership, and OleX token participation in the overall OleOle group of companies.
Responsibilities
Establish overall AI architecture
Lead initiatives including AskOle
Lead real-time multilingual translation
Develop AI-powered sports history and content generation systems
Develop the sports data engine
Requirements
Nice to have: building consumer AI platforms at scale
Nice to have: multilingual and multimodal AI engineering
Lead the design and governance of enterprise-wide Generative AI architecture, defining strategy, standards, and best practices for scalable, secure, and responsible AI solutions across cloud-native environments.
Responsibilities
Define enterprise-wide Generative AI architecture strategy, standards, and best practices
Design scalable and secure LLM-powered solutions using Azure OpenAI and Azure AI Services
Architect enterprise-grade RAG platforms leveraging vector databases, semantic search, and knowledge management systems
Design and govern Agentic AI ecosystems utilizing AI Agents, tool calling, orchestration, and autonomous workflows
Evaluate and select appropriate foundation models, embeddings, and multimodal architectures
Requirements
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or related field
Nice to have: Microsoft Certified: Azure Solutions Architect Expert
Nice to have: Microsoft Certified: Azure AI Engineer Associate
Nice to have: Microsoft Certified: Azure AI Fundamentals
Nice to have: Experience working with Fortune 500 enterprise AI transformation programs
Help shape the future of AI-powered industrial software solutions that support safe, reliable, and efficient operations across manufacturing, energy, and process industries.
Responsibilities
Lead the architecture, design, and technical direction of software solutions with a focus on AI-enabled capabilities and industrial software innovation.
Make sound technical decisions and clearly communicate options, trade-offs, and recommendations to technical and non-technical stakeholders.
Develop, review, and optimize complex software components to ensure quality, maintainability, scalability, and reliability.
Partner with product owners, architects, and cross-functional teams to translate customer and business needs into actionable technical solutions.
Establish and continuously improve engineering practices related to software quality, testing, security, performance, and delivery.
Requirements
Bachelor’s degree in Computer Science, Computer Engineering, Software Engineering, or a related field
Lead solution architecture and delivery of AI/GenAI solutions across India and US teams, ensuring compliance with regulatory frameworks and driving innovation with LLMs and cloud technologies.
Responsibilities
Design and implement end-to-end architecture for complex web applications
Oversee architectural decisions and provide technical leadership
Evaluate emerging technologies and recommend innovative solutions
Collaborate with stakeholders to gather requirements and translate them into technical specifications
Ensure technical solutions meet compliance, security, and scalability requirements
Requirements
Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or equivalent
Senior Data Scientist responsible for collecting, analyzing, and interpreting large datasets to drive data-driven decision-making and develop ML predictive models.
Locations (2)
Toronto, Ontario, Canada
Canada
Compensation
The expected range of compensation for this role is $77,000 to $117,000.
Responsibilities
Collect, clean, and transform large, complex datasets for analysis.
Build custom machine learning models and natural language processing systems using state-of-the-art techniques.
Leverage tools like TensorFlow, PyTorch, Kubernetes, and Nvidia Triton Servers to develop specialized large language models tailored to business needs.
Train, evaluate, and optimize models for accuracy, explainability, and ethical alignment.
Clearly communicate technical analysis and results to stakeholders using data visualizations, reports, and presentations.
CLIENT
Kforce/United Airlines
POSITION
GenAI Solutions Architect
LOCATION
Remote
DURATION
6 Month C2H
BILL RATE
$95/hr C2C
INTERVIEW TYPE
Video
VISA RESTRICTIONS
Must be able to convert without sponsorship
REQUIRED SKILLS
Required Qualifications
8+ years of experience in Software Engineering, Machine Learning, AI, or Solution Architecture roles.
Strong technical background in Machine Learning, NLP, Computer Vision, or related AI disciplines.
Hands-on experience architecting Generative AI solutions in enterprise environments.
Experience designing and implementing Retrieval-Augmented Generation (RAG) architectures.
Experience with Agentic AI frameworks and autonomous workflow orchestration.
Deep understanding of Large Language Models (LLMs) and prompt engineering methodologies.
Experience working within an AI Center of Excellence (CoE) or similar innovation-focused organization.
Proven track record of building successful AI POCs and advancing them to funded initiatives and production implementations.
Excellent communication, presentation, and stakeholder management skills.
Technical Requirements
Experience with several of the following technologies:
Large Language Models (OpenAI, Claude, Gemini, Llama, etc.)
RAG Architecture
Agentic AI Frameworks
Vector Databases:
Pinecone
Weaviate
Chroma
FAISS
Google Vertex AI
AWS SageMaker
Hugging Face
LangChain
LangGraph
LlamaIndex
Python
Machine Learning & Deep Learning Frameworks
Cloud Platforms (AWS, GCP, Azure)
API Design & Integration
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