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

EMBEDDED AI ENGINEERING POD

AI Implementation Engineer Role

Level: AI Implementation Engineer Senior / Advanced - 6+ years

Practice: Wissen GenAI

Locations: Mumbai / Bengaluru / New York - hybrid, embedded with delivery teams

Reports to: EMBEDDED AI PRACTICE Senior AI Engineering Specialist (Architect); Wissen GenAI Program Lead

Embedded inside enterprise delivery teams, you work closely with global, cross-regional teams to turn prioritized GenAI use cases into production software - building, integrating, and hardening Azure-based AI solutions and accelerating adoption within the teams you join.

You deliver production software and help the teams you join work faster.

As an embedded AI Implementation Engineer, you help convert prioritized use cases into shipped, governed, measurable software.

Key responsibilities

1. Build and ship.

Implement GenAI features end to end on Azure - RAG pipelines, agents, APIs, and UI integrations - against enterprise systems and data.

2. Embed and enable.

Work inside the delivery pods: pair with their engineers, remove blockers, and transfer GenAI skills so adoption sticks after you move on.

3. Productionize.

Add evaluation, observability, guardrails, caching, and CI/CD so prototypes become reliable, cost-efficient services.

4. Integrate securely.

Connect to enterprise data with correct access control, secrets management, and compliance with enterprise security standards and handling of sensitive data.

5. Iterate on quality.

Use evaluation results and user feedback to improve grounding, accuracy, latency, and cost.

6. Measure.

Track delivery and quality metrics that roll up to the program's targets.

Must-have qualifications

• 6+ years in software engineering, with 2+ years building GenAI/LLM applications in production.
• Strong Python (incl. async) and Java (the primary enterprise application stack; Spring a plus); solid API and systems design.
• Azure GenAI hands-on: Azure OpenAI, Azure AI Foundry, Azure AI Search for RAG, Azure AI Document Intelligence (IDP), and Prompt Flow.
• Agent frameworks: Microsoft Agent Framework / Semantic Kernel / AutoGen (or LangChain / LangGraph) and tool / function calling.

Preferred

• RAG fundamentals: embeddings, chunking, vector search, reranking, and grounding.
• Data platforms: Snowflake including Cortex AI (Cortex Search, LLM functions) and SQL, for accessing and grounding on enterprise data.
• Prompt engineering as versioned code; building and running evaluations.
• DevOps: Azure DevOps / GitHub Actions, Docker, AKS / Azure Functions, and observability.
• Financial services or other regulated environments.
• Front-end (React) for AI-assisted UX; streaming and token level operations.
• Azure AI Content Safety and responsible-AI practices.
• Certification: Azure AI Engineer Associate.

What success looks like - first 6 to 12 months

• Multiple GenAI features shipped to production within the embedded delivery pods.
• Measurable adoption and productivity uplift in the teams you support.
• Reusable components adopted from the architects' reference framework.
• Clear contribution to faster time-to-market and lower defect rates.

• Strong hands-on experience in Microsoft Azure Cloud.
• Good understanding of Azure services such as Compute, Storage, Event Hub, Event Subscription, Storage Queue, and PaaS services.
• Basic understanding of Azure AI Foundry and AI-related Azure service setup.
• Good Azure networking basics: VNet, subnet, routing, and basic troubleshooting.
• Strong knowledge of Terraform, especially:
• Terraform state
• plan / apply
• troubleshooting failures
• migration risks
• Terraform Enterprise concepts
• Strong Python coding capability, not just basic scripting.
• Experience using Python for API integration, automation, JSON/YAML handling, and internal tooling.
• Good understanding of CI/CD pipelines.
• Ability to troubleshoot pipeline failures.
• Comfortable with YAML and JSON.
• Ability to troubleshoot Azure infrastructure/platform issues.
• Ability to collect logs/evidence and coordinate with network/app/Microsoft support teams.
• Basic awareness of agentic AI / LLM concepts.
• Awareness of security and cost best practices.

Good to Have Skills

• Hands-on experience with Harness.
• Hands-on experience with Terraform Enterprise.
• Exposure to LangGraph / LangChain.
• Exposure to agentic AI workflows or skill creation.
• Exposure to Claude or enterprise LLM integrations.
• Knowledge of Azure ML Workspace, model registry, and managed endpoints.
• MLOps / LLMOps knowledge.
• FinOps / Azure cost optimization experience.
• Azure certifications: AZ-104, AZ-305, AZ-400, AZ-500.

Screening Priority:

Azure Cloud + Terraform + Python Coding + CI/CD Troubleshooting + YAML/JSON + Basic Agentic AI Awareness

As a techno-functional consultant you will be responsible for delivering and optimizing end-to-end solutions on the Dynamics 365 platform by bridging business requirements with technical implementation. The role focuses on configuring and enhancing Dynamics 365 Customer Service and Field Service modules, enabling seamless integration with SAP systems, and supporting multiple Power Pages portals for customers and subcontractors. The objective is to ensure efficient business process execution, secure and scalable integrations, and improved user experience through continuous collaboration with stakeholders, proactive problem-solving, and adherence to best practices and standards.

Tasks & Responsibilities: 

• Bridge the gap between business requirements and technical delivery across D365 Customer Service and Field Service
• Contribute to functional workshops, requirement gathering sessions, and solution design discussions with business stakeholders
• Good to have basic process understanding of SAP system.
• Configure D365 modules and implement light customizations — plugins, custom APIs, JS/TS, and Power Automate flows
• Design end-to-end solutions covering data model, SLAs, entitlements, and integrations
• Support UAT, produce functional specification document, and ensure solutions align with Microsoft best practices
• Training delivery and end-user adoption support post go-live
• Understanding of Model-Driven App design including entities, forms, views, dashboards, security roles etc.
• Strong client relationships to engage business and technical audiences equally
• Prepare and maintain key project documentation including Functional Specification Documents (FSD), Solution Design Documents (SDD), business process flows, and UAT documents
• Create and manage user stories, acceptance criteria, and test cases in Azure DevOps, ensuring traceability and alignment with business requirements

Education & Trainings + Certifications:

• At least 6 to 8 years of relevant experience in Dynamics 365, Field Service, Power Pages.
• Proven expertise with Dynamics 365 functional area, documentations, design, development, end-to-end implementations and solutions.

Technical know-how: 

• Strong understanding of Dynamics 365 Customer Service and Field Service modules, including case management, SLAs, entitlements, work orders, and scheduling
• Hands-on experience with Microsoft Dataverse, including entity design, relationships, forms, views, business rules, and security model
• Working knowledge of Model-Driven App development and customization
• Ability to implement light customizations using C#, .NET plugins, custom workflows, Web APIs, JavaScript/TypeScript
• Experience with Power Platform tools including Power Automate and basic exposure to Power Pages (portal configuration and customization)
• Good understanding of integration concepts, including REST/SOAP APIs and experience integrating D365 with external systems (preferably SAP)
• Experience with Azure DevOps for managing user stories, test cases, backlog, and release tracking
• Understanding of software development lifecycle (SDLC), Agile methodology, and UAT processes
• Knowledge of documentation standards including FSD, SDD, use cases, and business process mapping
• Good understanding of security concepts including role-based access, data security, and portal authentication mechanisms 

Soft Skills:

• Good team player skills to be able to work within a global team with shared global responsibilities
• Strong service orientation
• Solution-oriented and structured way of working
• Friendly, communicative and team-oriented player
• Business fluent English skills, spoken and written
• Intercultural competence 

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.

Software Engineer II to join Planview’s Keyedin team.

Planview is an enterprise software company focused on portfolio and work management, helping organizations plan, prioritize, and deliver work across strategy, teams, and technology. Its product portfolio spans project and portfolio management (PPM), enterprise agile planning, product portfolio management, and work management tools — including offerings like AdaptiveWork, Planview PPM Pro, ProjectPlace, Planview Viz, and Deliver (One2Team), plus its ProjectAdvantage (formerly Sciforma) product for project and resource management. The company serves a wide range of industries, from financial services to technology to government, helping large organizations connect strategy to execution and manage complex portfolios of projects, products, and resources.

About the Role:

You’ll work on a product that combines legacy and modern technologies, contributing across the full stack while helping shape future platform integrations, connectors, and AI-powered capabilities. You’ll also work directly on customer-facing tickets and real-world product challenges, gaining hands-on exposure to the application and its technology stack from day one.

What You’ll Work On

• Customer-facing development and product enhancements
• Platform integrations and connector development
• Cloud technologies and AI-enabled capabilities
• Maintenance and modernization of existing product functionality
• Collaboration on new technologies as the platform evolves

Must-Have Skills

• C#/.NET, MVC, VB.NET, Web API, and Dapper
• Angular, HTML, CSS, and JavaScript/TypeScript
• Unit testing using NUnit, Jasmine, and Karma
• IIS
• SQL Server, including functions, stored procedures, and scheduled jobs
• Experience with AI coding tools such as Claude, GitHub Copilot, or similar

Nice-to-Have Skills

• Integration testing
• Azure DevOps
• Power BI
• Cloud platforms such as Azure or AWS

Growth Opportunity

Over the next 1–2 years, you’ll have the opportunity to progress from handling customer-facing issues to owning complex technical problems and key product areas. You’ll build expertise across legacy and modern technologies, integrations, cloud, and AI, with a path toward leading technical initiatives, contributing to architectural and product decisions, mentoring engineers, and progressing toward a senior or technical leadership role.

Team Culture and Work Style

The Keyedin team is learning-focused, collaborative, and customer-focused. This role follows a hybrid work model with two days per week in the office and no shift work.

If this opportunity aligns with your experience and career goals, please share your updated resume and let me know a convenient time to connect.

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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