ideyaLabs is seeking a talented and innovative Generative AI Engineers with experience in leveraging Low-Code/No-Code (LCNC) platforms. This unique role will be at the forefront of developing and deploying cutting-edge generative AI models while utilizing LCNC tools to accelerate prototyping, integration, and application development. The ideal candidate will possess a strong understanding of generative AI techniques, proficiency in programming, and a passion for exploring the synergy between AI and rapid application development. Responsibilities: Generative AI Model Development & Deployment: Design, develop, train, and evaluate generative AI models for various applications (e.g., text generation, image synthesis, code generation, synthetic data generation). Implement and optimize generative AI models using relevant frameworks (e.g., TensorFlow, PyTorch, Transformers). Deploy and scale generative AI models on cloud platforms (e.g., AWS, Azure, GCP) or on-premise infrastructure. Stay up-to-date with the latest advancements in generative AI research and techniques. Low-Code/No-Code Platform Utilization: Utilize LCNC platforms (e.g., Zoho Creator, Microsoft Power Apps, OutSystems, Mendix, Quixy) to rapidly prototype and build applications that integrate with generative AI models. Develop user interfaces and workflows using LCNC visual development tools. Connect generative AI APIs and services to LCNC applications. Build and deploy data connectors and integrations between various systems using LCNC capabilities. Integration & Application Development: Design and implement robust APIs and integration strategies to connect generative AI models with other systems and applications. Collaborate with software engineers and data scientists to build end-to-end AI-powered solutions. Develop and maintain documentation for AI models, LCNC applications, and integration processes. Experimentation & Innovation: Research and experiment with new generative AI models, LCNC platforms, and integration techniques. Evaluate the feasibility and potential of applying generative AI to solve specific business problems. Contribute to the development of best practices and guidelines for using generative AI and LCNC tools. Collaboration & Communication: Work closely with cross-functional teams, including product managers, designers, and business stakeholders. Communicate technical findings and progress effectively to both technical and non-technical audiences. Participate in code reviews and knowledge-sharing activities. Qualifications: Education: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Experience: 3 + years of experience in developing and deploying machine learning models, with a focus on generative AI. Proven experience working with at least one or more Low-Code/No-Code development platforms (e.g., Zoho Creator, Microsoft Power Apps, OutSystems, Mendix, Quixy). Experience in building and consuming APIs (RESTful, etc.). Technical Skills: Strong programming skills in Python and experience with relevant AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn, Transformers). Solid understanding of deep learning concepts and architectures relevant to generative models (e.g., GANs, VAEs, Diffusion Models, Transformers). Experience with cloud platforms (e.g., AWS, Azure, GCP) and their AI/ML services. Familiarity with data preprocessing, feature engineering, and model evaluation techniques. Understanding of database concepts and SQL. Proficiency in using visual development tools and integration capabilities of LCNC platforms. Soft Skills: Strong problem-solving and analytical skills. Excellent communication and collaboration abilities. Ability to learn quickly and adapt to new technologies. Proactive and self-motivated with a strong sense of ownership. Passion for innovation and exploring the potential of generative AI. Preferred Qualifications: Experience with specific generative AI applications relevant to our industry (e.g., content generation, synthetic data for [mention industry]). Familiarity with containerization technologies (e.g., Docker, Kubernetes). Experience with MLOps practices and tools. Certifications in relevant AI/ML or LCNC platforms.

We are seeking a dynamic and results-oriented Marketing Head to spearhead all aspects of our web lead generation efforts. This role will be crucial in driving qualified traffic to our website, nurturing leads, and ultimately converting them into paying customers. The ideal candidate will be a data-driven marketer with a proven track record of success in B2B lead generation campaigns. Key Responsibilities: Develop and execute comprehensive digital marketing strategies to drive website traffic and generate high-quality leads. Manage and optimize all digital marketing channels , including: Search Engine Optimization (SEO): On-page and off-page optimization, keyword research, competitor analysis. Search Engine Marketing (SEM): Paid search campaigns (Google Ads, etc.), campaign optimization, and budget management. Social Media Marketing (SMM): Organic and paid social media campaigns on relevant platforms (LinkedIn, Twitter, etc.). Content Marketing: Develop and publish high-quality, engaging content (blog posts, white papers, case studies, webinars) to attract and nurture leads. Email Marketing: Develop and execute targeted email campaigns for lead nurturing and conversion. Website Analytics & Tracking: Monitor website traffic, track key metrics (e.g., conversion rates, cost per acquisition), and analyze data to optimize campaigns. Build and maintain a strong online presence through social media engagement, online communities, and industry events. Conduct market research to identify target audiences, competitor analysis, and industry trends. Manage the marketing budget effectively and efficiently. Collaborate with sales and other departments to ensure seamless lead flow and customer acquisition. Stay abreast of the latest digital marketing trends and technologies and continuously improve our marketing efforts. Qualifications: Bachelor's degree in Marketing, Business Administration, or a related field. 7+ years of experience in B2B digital marketing, with a strong focus on lead generation. Proven track record of success in driving website traffic and generating qualified leads. Strong understanding of SEO, SEM, SMM, and content marketing principles. Experience with CRM and marketing automation platforms (e.g., HubSpot, Marketo, Salesforce). Excellent analytical and data-driven decision-making skills. Strong project management and organizational skills. Excellent communication and interpersonal skills. Ability to work independently and as part of a team.

We are looking for a Senior .NET Developer with strong expertise in building scalable APIs and cloud-native solutions using AWS. This role focuses on logistics/transportation systems and requires leadership, mentoring, and hands-on development across modern .NET technologies. Key Technical Skills : Languages/Frameworks: C#, .NET Core, ASP.NET Core Web API Data Access: Entity Framework Core, LINQ, Dapper (Micro-ORM), PostgreSQL Cloud: AWS (Lambda, S3, SQS/SNS, X-Ray, Secrets Manager) Architecture: Clean Architecture, SOLID principles, Microservices Testing/Dev Tools: xUnit, Swagger, Git, Fluent Validation, Serilog Security: CORS, API Versioning, Secure Coding Practices Responsibilities: Design and develop high-performance APIs and microservices Build and deploy cloud-native apps using AWS services Lead code reviews, enforce clean code and architecture principles • Mentor junior developers and foster best practices • Collaborate on requirement analysis, planning, and estimation Maintain documentation, ensure test coverage and system reliability Preferred Experience & Domain : 3–4 years of hands-on experience in .NET development 2+ years working with AWS cloud infrastructure Experience in logistics or transportation domains (preferred) Technical leadership or mentoring background Soft Skills: Excellent problem-solving and debugging skills Strong communication and collaboration abilities Experience in planning, estimation, and project execution Passion for knowledge sharing and team growth Education & Certifications: Bachelor’s degree in Computer Science or related field Preferred: AWS or Microsoft .NET certifications

About the Role: We are seeking a DevOps Technical Lead with a strong background in infrastructure automation, cloud architecture, and a keen interest in Generative AI technologies. The ideal candidate will lead the development of an Infrastructure Agent powered by GenAI – capable of intelligent provisioning, configuration, observability, and self-healing. Key Responsibilities: Lead architecture & design of an intelligent Infra Agent leveraging GenAI capabilities. Integrate LLMs and automation frameworks (e.g., LangChain, OpenAI, Hugging Face) to enhance DevOps workflows. Build solutions that automate infrastructure provisioning , CI/CD , incident remediation , and drift detection . Develop reusable components and frameworks using IaC (Terraform, Pulumi, CloudFormation) and configuration management tools (Ansible, Chef, etc.). Partner with AI/ML engineers and SREs to design intelligent infrastructure decision-making logic. Implement secure and scalable infrastructure on cloud platforms ( AWS, Azure, GCP ). Continuously improve agent performance through feedback loops , telemetry , and fine-tuning of models. Drive DevSecOps best practices, compliance, and observability. Mentor DevOps engineers and collaborate with cross-functional teams (AI/ML, Platform, and Product). Required Qualifications: Bachelor's or Master’s degree in Computer Science, Engineering, or related field. 8+ years of experience in DevOps, SRE, or Infrastructure Engineering. Proven experience in leading infrastructure automation projects and technical teams. Expertise with one or more cloud platforms: AWS, Azure, GCP . Deep knowledge of tools like Terraform , Kubernetes , Helm , Docker , Jenkins , and GitOps . Hands-on experience integrating or building with LLMs / GenAI APIs (e.g., OpenAI, Anthropic, Cohere) . Familiarity with LangChain , AutoGen , or custom agent frameworks . Experience with programming/scripting languages: Python, Go, or Bash . Understanding of cloud security, policy as code , and monitoring tools (Prometheus, Grafana, Datadog). Preferred Qualifications: Experience building or fine-tuning LLM-based agents for operations or automation tasks. Contributions to open-source GenAI or DevOps projects. Understanding of MLOps pipelines and AI infrastructure. Certifications in DevOps, cloud, or AI technologies (e.g., AWS DevOps Engineer, Azure AI Engineer).

You are looking for a DevOps Technical Lead who will play a crucial role in leading the development of an Infrastructure Agent powered by Generative AI (GenAI) technology. In this role, you will be responsible for designing and implementing an intelligent Infra Agent that can handle provisioning, configuration, observability, and self-healing autonomously. Your key responsibilities will include leading the architecture and design of the Infra Agent, integrating various automation frameworks to enhance DevOps workflows, automating infrastructure provisioning and incident remediation, developing reusable components and frameworks using Infrastructure as Code (IaC) tools, and collaborating with AI/ML engineers and SREs to create intelligent infrastructure decision-making logic. You will also be expected to implement secure and scalable infrastructure on cloud platforms such as AWS, Azure, and GCP, continuously improve agent performance through feedback loops, telemetry, and model fine-tuning, drive DevSecOps best practices, compliance, and observability, as well as mentor DevOps engineers and work closely with cross-functional teams. To qualify for this role, you should hold a Bachelor's or Master's degree in Computer Science, Engineering, or a related field, along with at least 8 years of experience in DevOps, SRE, or Infrastructure Engineering. You must have proven experience in leading infrastructure automation projects, expertise with cloud platforms like AWS, Azure, GCP, and deep knowledge of tools such as Terraform, Kubernetes, Helm, Docker, Jenkins, and GitOps. Hands-on experience with LLMs/GenAI APIs, familiarity with automation frameworks, and proficiency in programming/scripting languages like Python, Go, or Bash are also required. Preferred qualifications for this role include experience in building or fine-tuning LLM-based agents, contributions to open-source GenAI or DevOps projects, understanding of MLOps pipelines and AI infrastructure, and certifications in DevOps, cloud, or AI technologies.,