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eSense

<div>
 Position Overview
 
 
 
 
 Mid-Level AI Engineer with strong hands-on experience in end-to-end AI system development, specializing in on-premises and private cloud AI deployments. This role focuses on building production-grade AI solutions using primarily local models, optimizing GPU-based training and fine-tuning pipelines, and developing scalable RAG, agentic, multimodal, and speech-enabled systems.
 
 
 
 
 Key Responsibilities&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 
 
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Analyze requirements and contribute to technical AI solution design.
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Strong programming skills in Python (mandatory).
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Experience in backend development (APIs, microservices, model serving).
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Hands-on experience with local LLM deployment and optimization.
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Experience in RAG system design and vector databases.
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Practical experience in model fine-tuning (LoRA / PEFT).
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Solid understanding of: Transformer architecture, quantization techniques, and embeddings with retrieval.
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Experience working in Linux environments.
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Participate in peer code reviews and team planning activities.
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Provide task estimations and deliver within approved timelines.
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Apply secure coding practices and participate in bug resolution with quality metrics in mind.
 
 
 
 
 Qualifications
 
 
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Bachelor&rsquo;s degree in computer science, Artificial Intelligence, Data Science, or related discipline.
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;2-5 years of experience in AI Engineering.
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Proficiency in C#, .NET Core and Python.
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Experience with Structured and Unstructured databases.
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Experience with Angular or other frontend technologies is a strong plus.
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Working knowledge of relational databases (i.e., SQL Server) and non-relational databases (i.e., Qdrant)
 
 
 &middot;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Familiarity with Git, RESTful services, and Agile development methodologies
 
</div>

AI Engineer

Finaira

<div>
 The Principal AI Engineer provides technical leadership and direction for a team of AI Engineer, overseeing the end-to-end development and deployment of significant AI initiatives. This role involves driving technical strategy, setting best practices, mentoring team members, and ensuring the delivery of high-quality, impactful AI solutions that align with business objectives.
 
 
 
 Focus:
 
 End-to-End Initiative Leadership, AI/ML Strategy &amp; Mentorship
 
 
 
 The difference you will make:
 
 
 
 <ul>
 <li>
 Provide technical leadership, guidance, and mentorship to a team of AI Engineer
 </li>
 <li>
 Architect, design, and oversee the implementation of complex AI/ML systems and platforms from conception to production
 </li>
 <li>
 Drive the technical roadmap for AI projects, translating business requirements into technical specifications and actionable plans
 </li>
 <li>
 Champion best practices in AI/ML engineering, MLOps, software development, code quality, and testing
 </li>
 <li>
 Lead technical discussions, architectural reviews, and problem-solving sessions within the team and across departments
 </li>
 <li>
 Collaborate closely with product management, data science, and other engineering teams to define project scope, technical feasibility, and resource allocation
 </li>
 <li>
 Identify and evaluate new technologies, tools, and methodologies to enhance the team's capabilities and efficiency
 </li>
 <li>
 Conduct performance evaluations and provide constructive feedback to team members, contributing to their professional growth
 </li>
 <li>
 Act as a primary technical point of contact for stakeholders regarding AI solutions
 </li>
 <li>
 Hands-on contribution to critical code components, architectural design, and complex problem-solving
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 
 What you will bring to the role:
 
 
 
 
 Education:
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field. Master's degree or Ph.D. highly preferred
 
 
 </li>
 </ul>
 
 Experience:
 
 
 
 <ul>
 <li>
 8+ years of extensive experience in AI/ML engineering, with at least 2-3 years in a technical leadership or lead engineer role, successfully leading significant AI projects from end-to-end
 
 
 </li>
 </ul>
 
 Technical Skills:
 
 
 
 <ul>
 <li>
 Expert proficiency in Python and deep expertise in multiple AI/ML frameworks (e.g., TensorFlow, PyTorch, Keras)
 </li>
 <li>
 Demonstrated experience in designing and implementing large-scale, production-grade AI systems, including distributed training and serving
 </li>
 <li>
 In-depth knowledge and practical experience with MLOps principles, tools, and platforms (e.g., Kubeflow, MLflow, Airflow, Docker, Kubernetes)
 </li>
 <li>
 Strong architectural skills for building robust, scalable, and maintainable AI infrastructures
 </li>
 <li>
 Proficiency in cloud environments (AWS, Azure, GCP) and their AI/ML services
 </li>
 <li>
 Excellent understanding of data engineering principles, data governance, and database technologies
 </li>
 <li>
 Ability to evaluate and make sound technical decisions on complex trade-offs
 
 
 </li>
 </ul>
 
 Soft Skills:
 
 
 
 <ul>
 <li>
 Exceptional leadership, communication, and presentation skills, with the ability to influence and persuade stakeholders at all levels, including executive leadership
 </li>
 <li>
 Proven ability to think strategically and translate complex business challenges into innovative and impactful data science initiatives
 </li>
 <li>
 Strong mentoring and coaching skills, with a passion for developing the talents of junior team members
 </li>
 <li>
 Excellent collaboration and negotiation skills, with the ability to work effectively across diverse, cross-functional teams and build strong relationships
 
 
 </li>
 </ul>
 Finaira is an Equal Opportunity Employer and is committed to providing a workplace free of discrimination and harassment. All employment decisions are based on business needs, job requirements, and individual qualifications, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other status protected by the laws or regulations in the locations where we operate.
</div>

Principal AI Engineer

<div>The Principal AI Engineer provides technical leadership and direction for a team of AI Engineer, overseeing the end-to-end development and deployment of significant AI initiatives. This role involves driving technical strategy, setting best practices, mentoring team members, and ensuring the delivery of high-quality, impactful AI solutions that align with business objectives. 
Focus: End-to-End Initiative Leadership, AI/ML Strategy &amp; Mentorship
The difference you will make:<ul><li>
Provide technical leadership, guidance, and mentorship to a team of AI Engineer.</li><li>
Architect, design, and oversee the implementation of complex AI/ML systems and platforms from conception to production.</li><li>
Drive the technical roadmap for AI projects, translating business requirements into technical specifications and actionable plans.</li><li>
Champion best practices in AI/ML engineering, MLOps, software development, code quality, and testing.</li><li>
Lead technical discussions, architectural reviews, and problem-solving sessions within the team and across departments.</li><li>
Collaborate closely with product management, data science, and other engineering teams to define project scope, technical feasibility, and resource allocation.</li><li>
Identify and evaluate new technologies, tools, and methodologies to enhance the team's capabilities and efficiency.</li><li>
Conduct performance evaluations and provide constructive feedback to team members, contributing to their professional growth.</li><li>
Act as a primary technical point of contact for stakeholders regarding AI solutions.</li><li>
Hands-on contribution to critical code components, architectural design, and complex problem-solving.</li></ul> 

Requirements 
What you will bring to the role:
Education:<ul><li>
Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field. Master's degree or Ph.D. highly preferred.</li></ul>
Experience:<ul><li>
8+ years of extensive experience in AI/ML engineering, with at least 2-3 years in a technical leadership or lead engineer role, successfully leading significant AI projects from end-to-end.</li></ul>
Technical Skills:<ul><li>
Expert proficiency in Python and deep expertise in multiple AI/ML frameworks (e.g., TensorFlow, PyTorch, Keras).</li><li>
Demonstrated experience in designing and implementing large-scale, production-grade AI systems, including distributed training and serving.</li></ul><ul><li>
In-depth knowledge and practical experience with MLOps principles, tools, and platforms (e.g., Kubeflow, MLflow, Airflow, Docker, Kubernetes).</li><li>
Strong architectural skills for building robust, scalable, and maintainable AI infrastructures.</li><li>
Proficiency in cloud environments (AWS, Azure, GCP) and their AI/ML services.</li><li>
Excellent understanding of data engineering principles, data governance, and database technologies.</li><li>
Ability to evaluate and make sound technical decisions on complex trade-offs.</li></ul>
Soft Skills:<ul><li>
Exceptional leadership, communication, and presentation skills, with the ability to influence and persuade stakeholders at all levels, including executive leadership.</li><li>
Proven ability to think strategically and translate complex business challenges into innovative and impactful data science initiatives.</li><li>
Strong mentoring and coaching skills, with a passion for developing the talents of junior team members.</li><li>
Excellent collaboration and negotiation skills, with the ability to work effectively across diverse, cross-functional teams and build strong relationships.</li></ul>
Finaira is an Equal Opportunity Employer and is committed to providing a workplace free of discrimination and harassment. All employment decisions are based on business needs, job requirements, and individual qualifications, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other status protected by the laws or regulations in the locations where we operate.</div>

<div>The Senior AI Engineer is a senior individual contributor with deep expertise in a specific domain of AI/ML, responsible for tackling the most complex technical challenges, driving architectural decisions for critical AI components, and setting technical standards. This role requires a blend of advanced research understanding and robust engineering skills to bring cutting-edge AI innovations into production.
The difference you will make<ul><li>
Act as a subject matter expert in one or more specialized AI/ML domains (e.g., Generative AI, Explainable AI, Large Language Models, Reinforcement Learning, Real-time Anomaly Detection).
</li><li>Lead the design and implementation of highly scalable, fault-tolerant, and high-performance AI systems and infrastructure.
</li><li>Evaluate and integrate new AI/ML research, algorithms, and technologies into product development.
</li><li>Drive continuous improvement in MLOps, model monitoring, and model governance frameworks.
</li><li>Provide expert technical guidance and mentorship to other AI Engineer 1s and Associates.
</li><li>Conduct complex performance tuning, optimization, and debugging of AI/ML models and pipelines.
</li><li>Participate in strategic planning for AI initiatives, identifying opportunities for technological advancement.
</li><li>Influence technical direction and architecture discussions within the AI/ML team and across engineering.
</li><li>Lead code reviews for critical components, ensuring architectural integrity, performance, and maintainability.</li></ul> 

Requirements 
Education:
<ul><li>Bachelor&rsquo;s degree or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a closely related quantitative field.
</li></ul>Experience:
<ul><li>5+ years of progressive experience in AI/ML engineering, with a proven track record of designing and deploying complex AI systems into production.
</li><li>Demonstrated deep expertise in a specific AI sub-field.</li></ul>
Technical Skills:
<ul><li>Expert-level proficiency in Python and advanced ML/DL frameworks (e.g., PyTorch, TensorFlow, JAX).
</li><li>Extensive experience with cloud-native AI/ML services and distributed computing frameworks (e.g., Spark, Ray).
</li><li>Deep understanding and hands-on experience with MLOps best practices, including CI/CD, model serving, and monitoring in production environments.
</li><li>Strong architectural design skills for complex data pipelines and scalable AI inference systems.
</li><li>Proficiency in system design, distributed systems, and performance optimization.
</li><li>Ability to critically evaluate and apply academic research to real-world problems.</li></ul>
Soft Skills:
<ul><li>Strong ownership and accountability for assigned work.
</li><li>Clear and professional verbal and written communication.
</li><li>Effective time management and task prioritization. o Analytical thinking and problem-solving skills.
</li><li>Ability to work independently, collaborate effectively and mentor junior team members.
</li><li>Ability to actively listen to customers and accurately understand their needs, expectations, and challenges.
</li><li>Adaptability and learning agility in a fast-paced environment.
</li><li>Strong attention to detail and a commitment to quality.
</li><li>Receptiveness to feedback and continuous improvement mindset</li></ul>
Finaira is an Equal Opportunity Employer and is committed to providing a workplace free of discrimination and harassment. All employment decisions are based on business needs, job requirements, and individual qualifications, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other status protected by the laws or regulations in the locations where we operate.</div>

Senior AI Engineer

BayanTech

<div><div>Job Description :
 
 
<ul><li>Design, develop, and deploy AI agents capable of performing autonomous tasks.</li></ul></div><ul><li>Build and fine-tune solutions using LLMs (e.g., OpenAI, Gemini, Claude, Mistral, LLaMA).</li><li>Proficient in Retrieval-Augmented Generation (RAG) systems and experienced with vector databases, leveraging these technologies to enhance AI model performance and scalability</li><li>Implement communication between agents using agent orchestration frameworks.</li><li>Automate workflows for sales, project management, accounting, and localization.</li><li>Collaborate with backend and frontend teams to integrate AI services.</li><li>Conduct prompt engineering and evaluation of model outputs.</li><li>Ensure the scalability and performance of AI systems in production environments.</li></ul> 

Job Requirement : 
 
<ul><li>1+ years of experience in AI/ML engineering or applied NLP.</li><li>Strong experience with LLMs and frameworks like LangChain, AutoGen, or CrewAI.</li><li>Solid Python skills; familiarity with FastAPI or Flask is a plus.</li><li>Experience with vector databases (e.g., Pinecone, Weaviate, ChromaDB).</li><li>Experience deploying models using Docker or cloud environments.</li><li>Understanding of multi-agent systems and conversational workflows.</li><li>Familiarity with version control (Git) and CI/CD practices.</li></ul></div>

Flatgigs

<div>
 
 The Role
 
 
 
 The Forward Deployed AI Engineer will work directly with clients and senior engineers to build AI-powered systems inside real enterprise environments. This role is ideal for a strong junior engineer who wants to work on practical AI systems, enterprise data, agents, retrieval, workflow automation, and context graphs. You will help connect to client systems, process messy real-world data, build prototypes, and turn business problems into working software.
 
 
 The work is hands-on and client-facing:
 
 
 <ul>
 <li>
 Understand operational workflows and convert them into technical artifacts
 </li>
 <li>
 Connect to real enterprise systems and data sources
 </li>
 <li>
 Build context-aware AI agents, retrieval systems, and automation prototypes
 </li>
 <li>
 Help move the best prototypes toward reliable production deployments
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 
 Build context graphs.
 
 Help ingest, clean, structure, and connect data from enterprise systems into context graph. This may include structured databases, PDFs, spreadsheets, tickets, CRM data, analytics events, Slack or Teams exports, meeting transcripts, operational workflows, and other internal knowledge sources.
 
 
 
 Develop AI and agentic workflows.
 
 Build AI pipelines and agent-based systems that can reason over enterprise context, identify patterns, surface workflow gaps, and suggest or trigger automations. This may involve LLMs, retrieval systems, structured extraction, tool use, LangGraph-style workflows, and agent harnesses.
 
 
 
 Connect to enterprise systems
 
 . Integrate with client infrastructure such as databases, APIs, cloud storage, document repositories, analytics tools, ticketing systems, and internal applications.
 
 
 
 Prototype automation opportunities.
 
 Rapidly build proof-of-concepts that show how AI can improve a client's operations - for example, process documentation, workflow discovery, incident management, document extraction, customer journey analysis, or operational decision support.
 
 
 
 Turn messy business problems into software.
 
 Work with senior engineers and business stakeholders to translate ambiguous operational problems into technical designs, data models, prompts, pipelines, and deployed applications.
 
 
 
 Support production deployments.
 
 Help build reliable, maintainable systems that can run in production environments, including client cloud environments when needed.
 
 
 
 Ideal Candidate
 
 
 
 We are looking for a strong junior software engineer who is excited about applied AI and wants to build real systems, not just experiments.
 
 
 You do not need to be an expert in every area below, but you should be curious, technical, and comfortable learning quickly.
 
 
 
 Technical Background
 
 
 
 <ul>
 <li>
 Strong Python fundamentals
 </li>
 <li>
 Basic backend development experience
 </li>
 <li>
 Familiarity with APIs, databases, and cloud services
 </li>
 <li>
 Interest in LLMs, agents, retrieval, structured outputs, and tool-calling
 </li>
 <li>
 Familiarity with data pipelines and messy real-world datasets
 </li>
 <li>
 Experience with FastAPI, LangChain, LangGraph, vector databases, document processing, or knowledge graphs is a plus
 </li>
 <li>
 AWS experience is a plus
 </li>
 <li>
 Experience with enterprise data, analytics, or workflow automation is a strong plus
 
 
 </li>
 </ul>
 
 What Makes Someone Successful In This Role
 
 
 
 <ul>
 <li>
 You like figuring out how businesses actually operate
 </li>
 <li>
 You are comfortable working with incomplete, messy, or poorly documented data
 </li>
 <li>
 You can move quickly from vague requirements to a working prototype
 </li>
 <li>
 You care about building useful systems, not just impressive demos
 </li>
 <li>
 You communicate clearly with both engineers and non-technical stakeholders
 </li>
 <li>
 You are curious about how AI agents can interact with real tools, data, and workflows
 </li>
 <li>
 You want to learn how to deploy AI into real enterprise environments
 
 
 </li>
 </ul>
 
 Why This Role Is Interesting
 
 
 
 You will work on the frontier of practical enterprise AI: connecting AI agents to real company context and using that context to discover and automate high-value workflows.
 
 
 This is a hands-on engineering role for someone who wants to grow into building production-grade AI systems across data, agents, infrastructure, and enterprise software
</div>

Forward Deployed AI Engineer

Bayantech

<div>
 
 Job Description :
 
 
 
 <ul>
 <li>
 Design, develop, and deploy AI agents capable of performing autonomous tasks.
 </li>
 <li>
 Build and fine-tune solutions using LLMs (e.g., OpenAI, Gemini, Claude, Mistral, LLaMA).
 </li>
 <li>
 Proficient in Retrieval-Augmented Generation (RAG) systems and experienced with vector databases, leveraging these technologies to enhance AI model performance and scalability
 </li>
 <li>
 Implement communication between agents using agent orchestration frameworks.
 </li>
 <li>
 Automate workflows for sales, project management, accounting, and localization.
 </li>
 <li>
 Collaborate with backend and frontend teams to integrate AI services.
 </li>
 <li>
 Conduct prompt engineering and evaluation of model outputs.
 </li>
 <li>
 Ensure the scalability and performance of AI systems in production environments.
 
 
 
 </li>
 </ul>
 
 Job Requirement :
 
 
 
 <ul>
 <li>
 1+ years of experience in AI/ML engineering or applied NLP.
 </li>
 <li>
 Strong experience with LLMs and frameworks like LangChain, AutoGen, or CrewAI.
 </li>
 <li>
 Solid Python skills; familiarity with FastAPI or Flask is a plus.
 </li>
 <li>
 Experience with vector databases (e.g., Pinecone, Weaviate, ChromaDB).
 </li>
 <li>
 Experience deploying models using Docker or cloud environments.
 </li>
 <li>
 Understanding of multi-agent systems and conversational workflows.
 </li>
 <li>
 Familiarity with version control (Git) and CI/CD practices.
 
 </li>
 </ul>
</div>

AI Engineer (Hybrid)

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