Dynamic CRM Developer Gen AI

About the Role

We are a 25-year-old company building toward a technology-centered workforce where AI agents and automation handle more of the day-to-day work, supported by people with specialized expertise.

We are automating our existing workflows, expanding our use of agentic AI, launching a sister company next year, and building a fleet of Hermes AI agents to delegate and manage work.

We are looking for a hands-on AI Systems Architect & Company Technology Lead to help build, connect, and continuously improve these systems.

Key Responsibilities

·       Own and improve our Microsoft 365 technology environment and AI-powered workflows.

·       Build automations connecting email, meetings, Planner, and other business systems.

·       Research, test, implement, and maintain AI tools and integrations.

·       Build and manage the Hermes agent fleet, including shared memory, delegation rules, workflows, and reporting.

·       Connect AI agents to business systems and SaaS platforms using APIs, webhooks, databases, and automation tools.

·       Help build an internal agentic marketing department by selecting and connecting the right AI tools.

·       Continuously troubleshoot, improve, and document our technology systems.

·       Help apply these systems as the company expands into new ventures.

Must-Haves

·       Strong technical problem-solving and self-teaching ability.

·       Solid hands-on experience building, configuring, and managing AI agents.

·       Experience connecting AI agents and multiple SaaS platforms using APIs, webhooks, databases, and automation tools.

·       Comfortable with Python, JavaScript, or similar.

·       Ability to independently research, build, test, troubleshoot, and improve systems.

·       Strong interest in AI, automation, and emerging technology.

This is a rapidly changing field therefore Direct experience working with actual Hermes agents is not required. However, hands-on experience working with AI agents is required.

What we need is someone who already understands the fundamentals of deploying AI agents, giving them instructions and tools, connecting them to other systems, and making them work reliably in a real business environment.

The Opportunity

This is an opportunity to help us discover and implement what is actually possible with AI today, and to lead the process of expanding workflows along with the rapidly advancing capabilities — this role is not only to implement a technology that has already been figured out.

AI Developer  

Primary Skill-set (Must have) 

• Generative AI Expertise: 2-3 years of experience in designing and implementing generative AI solutions, including knowledge of various generative and autoregressive models. Ability to apply generative AI techniques to diverse use cases such as image generation, text generation, and creative content synthesis. 

• 2 years of experience in prompt engineering, fine tuning, agentic framework, GenAI SDK’s 

• 1-2 years of experience in Agentic AI frameworks like Autogen, Lanngraph, MS Agent SDK, A2A, MCP, A2P, memory concepts, multi agent orchestration 

• 7+ years of experience in Python 

• 5+ years of experience in software development 

• Azure Proficiency: 3-5 years of experience with Azure cloud services relevant to AI, including Azure Machine Learning, Azure Cognitive Services, Azure Databricks, and Azure Kubernetes Service (AKS). 2+ years of experience in Azure's capabilities to architect end-to-end AI solutions and optimize performance. 

• Architecture Design: 3-5 years of skills with the ability to design scalable, reliable, and cost-effective architectures for AI solutions. Proficiency in designing distributed systems, microservices architectures, and containerized solutions using technologies such as Docker and Kubernetes. 

Secondary Skills (Good to have) 

• Security and Compliance: Understanding of security principles and best practices in AI development, with the ability to implement security controls, encryption mechanisms, and access management policies to protect AI models and sensitive data. 

• Integration and Deployment: Proficiency in implementing CI/CD pipelines, automation scripts, and infrastructure as code (IaC) using tools such as Azure DevOps, Terraform, or Ansible. Experience in containerization and orchestration of AI workloads using Docker and Kubernetes. 

• Software Development: Strong programming skills in languages such as Python, with experience in developing AI applications, RESTful APIs, and microservices architectures. Familiarity with software development methodologies such as Agile or Scrum. 

• Communication and Presentation: Excellent communication skills with the ability to convey complex technical concepts to non-technical stakeholders. Experience in preparing and delivering technical presentations, architecture diagrams, and documentation to communicate architectural decisions and design rationale effectively. 

Role Descriptions: Good dynamics skills 365 skills

Essential Skills: Good dynamics skills 365 skills

Skills: Digital : Microsoft Dynamics 365 CRM Functional

Experience Required: 8-10

7 to 14 years

location bangalore

Looking for an Architect with strong experience in AI and Data Engineering, preferably with hands-on experience in Generative AI (GenAI). Candidates with experience in any cloud platform (AWS, Azure, or GCP) will be considered, 

Job Details

Position Title: AI Evangelist

Role Purpose

We are seeking a highly experienced AI Evangelist & Core AI Engineer who combines deep technical expertise in Artificial Intelligence with the ability to influence, educate, demonstrate, and accelerate AI adoption across the enterprise.

The role requires deep understanding of AI, Machine Learning, Deep Learning, Generative AI, Large Language Models, Agentic AI, AI engineering, and modern software development practices, combined with significant hands-on experience implementing scalable AI applications in complex enterprise environments.

Key Responsibilities

1. Core AI Engineering & Architecture

• Design, develop, and implement enterprise-grade AI and Generative AI applications.
• Build scalable applications using LLMs, multimodal models, AI agents, RAG, vector databases, knowledge graphs, APIs, and enterprise data platforms.
• Architect AI solutions capable of supporting enterprise-scale workloads with appropriate considerations for:
• Scalability
• Reliability
• Security
• Performance
• Observability
• Cost optimization
• Governance
• Develop and implement advanced Retrieval-Augmented Generation (RAG) architectures including hybrid search, reranking, metadata filtering, semantic retrieval, and knowledge grounding.
• Build multi-agent and agentic AI applications capable of reasoning, tool usage, workflow execution, orchestration, and enterprise system integration.
• Design AI applications integrating structured and unstructured enterprise information.
• Evaluate architecture choices between commercial models, open-source models, small language models, domain-specific models, and hosted AI platforms.
• Implement model routing, prompt orchestration, caching, guardrails, evaluation pipelines, and fallback strategies.
• Work closely with cloud, platform, security, enterprise architecture, DevOps, and application engineering teams.

2. Deep AI / ML / DL Expertise

The candidate should have strong conceptual and practical understanding across the modern AI technology landscape, including:

• Artificial Intelligence /Machine Learning/ Deep Learning/ Neural Networks /LLM/SLM/RAG/Graph RAG / MLOps / LLMOps / GenAIOps

3. Generative AI & LLM Engineering

• Build production-grade applications utilizing leading commercial and open-source LLM ecosystems.
• Design scalable LLM platforms supporting multiple enterprise applications and use cases.
• Develop reusable LLM services, APIs, components, agent frameworks, and reference architectures.

4. AI Agents & Automation

• Design and implement AI agents and agentic workflows that automate complex business and engineering processes.
• Build agents capable of interacting with enterprise applications, APIs, databases, documents, development environments, and workflow platforms.
• Evaluate emerging agent architectures and orchestration frameworks pragmatically.
• Develop reusable patterns for:
• Single-agent systems
• Multi-agent systems
• Human-in-the-loop workflows
• Autonomous workflows
• Tool-calling agents
• Coding agents
• Enterprise knowledge agents
• Establish appropriate controls for AI agent identity, permissions, auditability, security, and human oversight.

5. AI-Enabled Software Engineering

Drive adoption of AI throughout the Software Development Life Cycle.

Summary -

• We are looking for a Cloud Infrastructure Engineer to build and operate the Azure foundation for our AI workloads and serve as the working bridge between the Cloud Infrastructure and Data teams. You will own Terraform-driven Azure infrastructure, DevOps pipelines, and hands-on platform components, including Azure AI Foundry, Model Context Protocol (MCP) servers, and Databricks.

Responsibilities -

• Build and maintain Azure infrastructure as code with Terraform, including reusable modules and multi-environment patterns.
• Provision and operate Azure AI Foundry hubs and projects, including model deployments, data connections, and identity and network configuration.
• Design and secure MCP servers that expose internal tools and data to AI agents.
• Partner with the Data team to deploy and configure Databricks workspaces, including VNet injection, private endpoints, Entra ID integration, and Unity Catalog.
• Own CI/CD pipelines in Azure DevOps or GitHub Actions for infrastructure and AI platform deployments.
• Enforce guardrails for AI workloads, including Key Vault secrets management, managed identities, and network isolation.
• Monitor platform health, reliability, and cost with Azure Monitor and Log Analytics.
• Triage cross-team platform requests, document reference patterns, and remove blockers between Cloud and Data teams.\

Requirements -

• 4 to 8 years of experience in cloud infrastructure or platform engineering.
• Strong hands-on Azure experience, including networking, Entra ID, RBAC, and managed identities.
• Advanced Terraform skills, including module design and state management.
• Working knowledge of DevOps practices, CI/CD, and Git-based workflows.
• Working knowledge of Azure AI Foundry or Azure OpenAI, including access control and network integration.
• Practical understanding of MCP and the security considerations for connecting AI agents to enterprise systems.
• Hands-on Databricks platform experience, including workspace deployment, Unity Catalog, and cluster configuration.
• Scripting skills in Python, PowerShell, or Bash.
• Experience working within SOC 2 Type II or similar control frameworks.

Preferred Qualifications -

• Experience with RAG architectures or Azure AI Search.
• Experience with GPU capacity and quota planning in Azure.

Job Description-

Location- Bengaluru

Experience-5-7 years

Wissen is building the engineering team for RES Modernization, a corporate services programme at a leading global financial services firm, rebuilding the lease and real estate management platform on a cloud stack with AI and agentic capability designed in rather than bolted on. The AI Solution Engineer builds that product: .NET services and APIs at the core, Python wherever the AI, retrieval and data work lives. We want a strong .NET engineer who has moved into Python, not a Python specialist who once touched C#.

• Build features end to end on a .NET codebase: C# and ASP.NET Core services, the APIs above them, and the React or Angular front end where a feature needs one.
• Write the Python that carries the AI work — retrieval and grounding, prompt and agent orchestration, evaluation harnesses, and the pipelines that feed them.
• Put LLM and agentic capability into real product workflows, with the grounding, guardrails and cost and latency budgets a regulated environment demands.
• Take your work through the client's engineering and change review: design notes, test evidence, security and code-quality gates.
• Work with the stream's data and integration engineers on the Snowflake and integration layer the product reads from.

Position Summary

We are looking for an experienced Enterprise Architect to define and deliver enterprise-scale digital experience architectures leveraging AI/ML capabilities, data platforms, and modern cloud technologies. The role involves partnering with senior business and technology stakeholders to translate business objectives into scalable architectures, strategic roadmaps, and technology solutions.

The ideal candidate will have strong expertise in enterprise architecture, cloud-native technologies, AI-driven customer experiences, and digital marketing platforms, along with the ability to lead architecture initiatives across cross-functional teams.

Key Responsibilities

• Enterprise Strategy & Roadmaps: Define digital, data, and AI strategies, translating business vision into actionable architecture roadmaps aligned with business goals and KPIs.
• Architecture Design: Design end-to-end enterprise and solution architectures integrating digital experience platforms, customer data platforms, AI/ML capabilities, and cloud services.
• Cloud & Technology Architecture: Recommend scalable, secure, and resilient architectures using cloud-native, API-first, microservices, event-driven, and serverless principles across Azure, AWS, or other public cloud platforms.
• AI & Data Architecture: Define architectures for customer data platforms, identity and profile management, data ingestion, governance, personalization, journey orchestration, and AI-powered experiences.
• Architecture Governance: Establish architecture standards, reference architectures, governance frameworks, and operating models to ensure consistency, security, and sustainable technology adoption.
• Stakeholder Management: Collaborate with business leaders, engineering teams, data architects, developers, and data scientists to drive architecture alignment and execution.
• Executive Communication: Lead architecture workshops, visioning sessions, and roadmap presentations, communicating technical recommendations and trade-offs to senior leadership.
• Practice Development: Contribute to reusable architecture assets, mentor architects and consultants, and support presales activities, solutioning, estimations, and proposals.

Required Skills & Experience

• Proven experience in enterprise architecture, solution architecture, and developing enterprise architecture models and roadmaps.
• Strong understanding of architecture frameworks and principles, including TOGAF, SOA, and API-led architecture.
• Hands-on experience with public cloud architecture and services, particularly Microsoft Azure and/or AWS.
• Experience designing and integrating AI-powered solutions, with knowledge of LLMs, prompt engineering, RAG, and model evaluation.
• Understanding of agentic workflows, tool-using agents, and enterprise AI governance, observability, and reliability.
• Experience working with software engineers, application developers, data architects, and data science/ML teams to deliver end-to-end solutions.
• Ability to translate business requirements and strategic vision into technical architectures and implementation roadmaps.
• Strong stakeholder management, leadership, presentation, and communication skills, including experience engaging with senior executives.
• Ability to lead architecture execution across multidisciplinary teams and communicate complex technical concepts to diverse audiences.

Good to Have

• Experience with Adobe Experience Cloud, Adobe Experience Platform, or one or more digital experience solutions.
• Previous experience with other digital marketing and customer experience platforms.
• Experience with customer data platforms, personalization, omnichannel engagement, and marketing optimization initiatives.
• Experience supporting consulting engagements, presales, and enterprise transformation initiatives.

Additional Requirement

- Willingness to travel up to 50%, depending on business and client requirements.

Required Skills:

• Strong C#/.NET development and experience building Agentic AI applications, workflow engines, automation systems, or tool-calling software.
• LLM/SLM integration with structured outputs and function calling.
• Third-party API/SDK integration.
• Asynchronous programming, concurrency, state machines, and fault handling.
• Windows application, service, or systems development.
• Authentication, permissions, secure software design, automated testing, and debugging.
• Bachelor's/Master's degree in Computer Science, Computer Engineering, or related field.

Preferred Skills:

• ONNX Runtime, Windows ML, DirectML, OpenVINO, or llama.cpp.
• Semantic Kernel, AutoGen, LangGraph, or MCP.
• PowerShell, Win32/WinRT, UI Automation, or Playwright.
• Knowledge graphs, vector retrieval, and agent memory.
• Model optimization, telemetry, diagnostics, sandboxing, and security.
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AI Architect – Enterprise AI & Generative AI ( Remote) - Contractual

Experience: 8+ years

Location: Remote, India

Employment Type: Contractual

Working Hours: 3:00 PM – 12:00 AM IST

Client Engagement: US-based client

About the Role

We are looking for a hands-on, client-facing AI Architect to lead the architecture, technical direction, and production implementation of enterprise AI and Generative AI solutions for a US-based client.

You should combine strong software engineering and cloud architecture fundamentals with practical experience building secure, scalable, and reliable AI applications. This role involves end-to-end technical ownership, from solution design and prototyping to production deployment and optimization. It is not a research-only, advisory-only, or prompt-writing position.

Key Responsibilities

• Lead end-to-end architecture and delivery of AI/ML and Generative AI solutions, from discovery and proof of concept to production rollout.
• Design LLM-powered applications using Retrieval-Augmented Generation (RAG), embeddings, vector databases, AI agents, and orchestration frameworks.
• Define data ingestion, chunking, retrieval, grounding, evaluation, and knowledge-refresh strategies.
• Select appropriate AI models and platforms based on quality, latency, cost, security, and operational requirements.
• Design cloud-native architectures, APIs, integrations, identity controls, monitoring, and resilient deployment patterns.
• Create architecture diagrams, technical designs, implementation roadmaps, and technical standards.
• Implement AI quality and safety measures, including hallucination mitigation, guardrails, access controls, and prompt-injection defenses.
• Guide engineering, data, ML, and DevOps teams through implementation, code reviews, troubleshooting, and go-live readiness.
• Lead technical discussions and design reviews with US client stakeholders.
• Establish production monitoring, CI/CD, versioning, incident handling, and performance and cost optimization practices.

Required Skills & Qualifications

• 8+ years of relevant experience in software engineering, AI/ML engineering, data engineering, or technology architecture.
• Proven experience personally architecting and deploying at least one enterprise-grade AI or Generative AI solution into production.
• Strong practical knowledge of LLMs, RAG, embeddings, vector databases, orchestration frameworks, and model evaluation.
• Hands-on experience with Python and APIs, including prototyping, code review, and troubleshooting.
• Experience with at least one major cloud platform: Microsoft Azure, AWS, or Google Cloud Platform (GCP).
• Understanding of data pipelines, SQL/NoSQL databases, containers, CI/CD, MLOps, and LLMOps.
• Knowledge of enterprise security, privacy, identity and access management, and responsible AI practices.
• Experience independently leading architecture workshops, design reviews, and technical discussions with US clients.
• Excellent written and spoken English, documentation, and stakeholder management skills.
• Availability to work from 3:00 PM to 12:00 AM IST and willingness to accept a contractual engagement.

Preferred Experience

• Azure AI Foundry, Azure OpenAI, Amazon Bedrock, or Google Vertex AI.
• Azure AI Search or equivalent retrieval tools.
• LangChain, LangGraph, Semantic Kernel, and agent/tool orchestration.
• Model fine-tuning, predictive ML, document intelligence, multimodal AI, or real-time AI applications.
• Experience in cloud modernization, enterprise integrations, data analytics, or technology consulting.
• Relevant AI/cloud architecture certifications and experience mentoring technical teams.

What Success Looks Like

• Designing secure, scalable, production-ready AI solutions rather than demos or conceptual presentations.
• Making sound technical decisions around feasibility, performance, reliability, cost, and AI risks.
• Taking ownership of architecture decisions and resolving technical blockers with limited supervision.
• Building trust with senior US stakeholders and collaborating effectively with India-based delivery teams.

Contract Details

• Initial engagement: Minimum 3 months, with extension subject to project requirements and performance.
• Working schedule: 3:00 PM – 12:00 AM IST.
• Potential permanent employment: After 18 months, the client may consider direct permanent employment at its sole discretion. Conversion is not guaranteed.

Mandatory Screening Criteria

Candidates should be able to:

• Explain an enterprise AI/GenAI solution they personally architected and deployed, including architecture, scale, evaluation, and business impact.
• Whiteboard an enterprise RAG or agentic solution covering data flow, security, authentication, authorization, monitoring, and cost controls.
• Discuss real-world model-quality issues, hallucinations, privacy risks, incidents, and architectural trade-offs.
• Lead a technical design review with US client stakeholders.
• Confirm acceptance of the working hours and contractual engagement.

Apply only if you have hands-on experience architecting and deploying enterprise AI/GenAI solutions in production.