Integration Support Engineer

We are looking for an integration engineer to assist our rapidly growing customer base. As part of our integration team, you will be the primary point of contact for all integrations. You would be responsible for helping our clients integrate with OneFin APIs, configuring our system for clients, and providing ongoing help to them to resolve any issues.

Application form: https://forms.gle/KbbeXxqhwpwnCzcDA

Responsibilities

• Understand and explain APIs to clients. Help clients integrate OneFin APIs. Research and identify solutions to issues during integration.
• Escalate unresolved issues to appropriate internal teams (e.g., software developers).
• Become a product expert for clients.
• Configure the OneFin system for customized usage by clients. Identify and write internal and external technical articles or knowledge-base entries, like typical troubleshooting steps, workarounds, or best practices, how-to guides, etc.
• Automate the solution of common issues using Python.
• Help live clients resolve issues and coordinate with the development team for issue resolution.

Requirements and Qualifications:

• BS/B.Tech. in Computer Science, Engineering, or an equivalent.
• Strong verbal and written communication skills.
• Experience in writing code in Python.
• Understanding web-based systems.
• Proficient in understanding and writing JSON.
• Experience in SQL databases.
• Experience working with REST APIs.
• Excellent analytical skills, passion for pinning down technical issues, and solving problems.
• Enjoys a fast-paced startup environment.

Primary Skills: Linux Administration, Production Support

Secondary Skills: Oracle SQL, Splunk, Grafana, AppDynamics, Cloud (OCP/AWS/Azure/GCP), Incident Management, AI/Automation.

Support Engineer – AI/ML & Education ERP

Company: iCloudEMS

Location: Remote / Work From Home

Employment Type: Full-Time

Experience: Freshers / 0–1 Year

About iCloudEMS

iCloudEMS is an Education ERP platform that helps universities, colleges, and educational institutions manage academic and administrative operations through integrated digital solutions.

We are looking for a motivated Support Engineer with an interest in AI/ML technologies to support clients using the iCloudEMS Education ERP platform. The ideal candidate should have basic knowledge of SQL/MySQL, web applications, troubleshooting, and AI/ML concepts, along with strong communication and problem-solving skills.

Key Responsibilities

• Provide first-level technical support through phone, email, and ticketing systems.
• Troubleshoot issues related to Admissions, Academics, Finance, HRMS, LMS, and Online Examination modules.
• Perform basic SQL/MySQL queries for data validation, troubleshooting, and issue analysis.
• Reproduce reported issues and coordinate with QA and Development teams for resolution.
• Test software functionality and verify bug fixes.
• Analyze API/web application issues and escalate complex technical problems.
• Assist with AI-powered features, AI/ML tools, and automation workflows where required.
• Support testing and validation of AI/ML-based features and applications.
• Create support documentation, FAQs, user guides, and knowledge-base articles.
• Assist with client onboarding, product demonstrations, and user training.
• Maintain clear communication with clients and ensure timely issue resolution.
• Continuously learn new ERP, AI/ML, database, and web technologies.

Required Skills

• Bachelor's degree in Computer Science, IT, BCA, MCA, B.Tech, or related field.
• Freshers or candidates with 0–1 year experience can apply.
• Basic knowledge of SQL/MySQL and relational databases.
• Basic understanding of web applications, APIs, and troubleshooting.
• Basic understanding of AI/ML concepts, Generative AI, or LLMs.
• Strong analytical and problem-solving skills.
• Good verbal and written communication.
• Ability to understand technical problems and explain solutions clearly.
• Willingness to learn AI/ML and emerging technologies.

Preferred Skills

• Basic knowledge of PHP, HTML, CSS, and JavaScript.
• Familiarity with OpenAI/LLM APIs, ChatGPT, prompt engineering, or AI tools.
• Basic knowledge of Python and AI/ML libraries is an advantage.
• Familiarity with ERP/EdTech applications.
• Knowledge of ticketing/helpdesk systems.
• Basic understanding of REST APIs and web services.

What You'll Gain

• Hands-on experience with a real-world Education ERP platform.
• Practical exposure to SQL, databases, APIs, web applications, and troubleshooting.
• Exposure to AI/ML, Generative AI, LLMs, and AI-powered ERP features.
• Experience working with Support, QA, Development, and Implementation teams.
• Client communication and enterprise software experience.
• Long-term career growth and learning opportunities.

Benefits

• Full-Time Employment
• Permanent Work From Home
• Learning and development opportunities
• Exposure to Education ERP + AI/ML technologies
• Collaborative work environment
• Career growth opportunities

Compensation: As per company norms

Why Join iCloudEMS?

Join iCloudEMS to work on a real-world Education ERP platform while gaining practical experience in technical support, SQL, web technologies, AI/ML, and enterprise software. This role is ideal for candidates who want to build a strong foundation in both technical support and emerging AI technologies.

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.

Location: Bangalore (Hybrid)

Experience: 4–8 Years

About the Role

At Twenty20 Systems, we are looking for a Senior Software Engineer (Integration) who can build and support scalable integrations across enterprise applications, APIs, and data systems.

This role is ideal for someone who is hands-on, technically strong, and excited to solve real integration challenges in a fast-paced environment. You will work closely with engineering, product, and delivery teams to build reliable integration solutions while contributing to architecture and engineering best practices.

What You’ll Do

• Design, develop, and maintain enterprise integrations, APIs, and automation workflows across internal and third-party systems.
• Build and manage integrations using Workato and other iPaaS/middleware platforms.
• Develop and optimize API-based services, data pipelines, and workflow automations for business-critical use cases.
• Work with product, engineering, and business teams to understand requirements and build scalable solutions.
• Troubleshoot, monitor, and improve integration performance in production environments.
• Build reusable components, connectors, and automation logic to improve delivery efficiency.
• Ensure integrations follow security, reliability, performance, and governance standards.
• Support delivery teams in resolving integration issues and improving system performance.

Requirements

• 4–6 years of experience in software engineering, middleware, or enterprise integrations.
• Strong hands-on experience in Workato (Boomi, MuleSoft, WSO2, TIBCO experience is a plus).
• Good understanding of REST/SOAP APIs, webhooks, OAuth, and connector-based integrations.
• Strong skills in JSON, XML, SQL, JavaScript/Python, and data transformation logic.
• Experience working with enterprise applications like Salesforce, NetSuite, Workday, Snowflake, Shopify, etc.
• Exposure to cloud platforms (AWS/Azure/GCP) and automation architectures is a plus.
• Good debugging, troubleshooting, and problem-solving skills.
• Ability to work in a fast-paced delivery-oriented environment with strong ownership.

What Your First 3 Months Will Look Like

• Take ownership of assigned integration projects and support ongoing delivery pipelines.
• Work on API integrations, automations, and troubleshooting real-time production scenarios.
• Collaborate with senior engineers and product teams to improve integration quality and performance.

Where You’ll Be in 6 Months

• Independently handling multiple integration workflows and delivery requirements.
• Contributing to reusable frameworks and engineering best practices.
• Becoming a key technical contributor for integration design and production support.
• Driving faster delivery through automation and optimized integration patterns.

Technical Lead 

Job Description 

Role Overview 

We are seeking a highly skilled Data Engineering Lead with minimum of 5 years of hands-on experience in Azure data engineering, data warehousing, and automation-driven  integration. The ideal candidate should be a proven technical lead, capable of driving end-to-end 

project delivery and working closely with customer teams. This is a Work from Office / Customer Site role. 

Roles and Responsibilities 

• Lead the design, development, and delivery of data engineering and automation projects. 

• Architect and implement ETL/ELT pipelines using Azure Data Factory. 

• Design and manage enterprise data warehouses including dimensional modeling and 

schema optimization. 

• Manage Azure components including Storage Accounts, Data Lakes, Azure SQL, and Synapse. 

• Drive automation initiatives across data ingestion and transformation workflows. 

• Collaborate with business and technical stakeholders to translate requirements into scalable solutions. 

• Mentor team members and enforce engineering best practices. 

• Serve as the technical anchor responsible for ensuring high-quality, on-time delivery. 

Skills and Qualification 

• Strong hands-on experience with Azure Data Factory, Azure Storage, Azure SQL/Synapse. 

• Deep understanding of data warehousing concepts: star/snowflake schemas, fact/dimension modeling. 

• Experience with automation-led data engineering solutions. 

• Strong troubleshooting, optimization, and analytical skills. 

• Excellent communication and stakeholder management abilities. 

• Proven experience as a Technical Lead leading teams and delivery. 

Must Have 

• Min of 5 years of relevant data engineering experience. 

• Strong Azure Data Engineering and Data Warehousing expertise. 

• Proven Technical Lead experience. 

• Ability to work from office and customer site. 

• Strong ownership mindset with a focus on quality and delivery excellence.

We are looking for a dynamic Data Engineer to join our team of technology enthusiasts. You will leverage data to drive strategic decision-making and pioneering solutions, working with complex datasets, collaborating closely with stakeholders, and transforming data into actionable insights to drive innovation.

Qualifications and Skills:

• Minimum 5 years of experience as a Data Engineer
• Hands-on experience with Azure cloud-based data solutions
• Expertise in database design and management, including SQL databases such as SQL Server
• Proficient in ETL (Extract, Transform, Load) design for data integration and processing
• Strong knowledge of data modeling principles and techniques
• Ability to analyze and translate data into actionable insights, reports, and visualizations
• Proficiency in Power BI for reporting and data visualization

Desirable Skills:

• Experience with Power BI Report Builder / Reporting Services
• Knowledge of statistical analysis or Data Science
• Experience within the UK Insurance industry is a plus
• Python or R coding skills

Responsibilities:

• Implement efficient data exchange between internal and external systems to increase efficiency and reduce re-keying and translation errors
• Support the Broking business by developing high-quality information resources, ensuring data availability and accessibility for decision-making
• Engineer data inputs and outputs from core applications and semi-structured remote service data through data syncs between data lake, ODS (SQL database), and leveraging Fabric and ADF
• Perform data engineering tasks including ingestion, cleansing, and collation from a wide range of internal and external sources
• Implement different methods of streaming data and create reconciliations for datasets
• Build analytical models to support reporting and analytics
• Collaborate with an agile delivery team to work on the backlog of specified work

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.

The role

A working product and a working deployment are two different things. You are the person who closes that gap.

You sit inside the client's head office. You get the deployment live, you get their teams using the dashboards, and you own whether the AI is returning something worth acting on. Every client is different: different languages on the floor, different store noise, different vocabulary for the same product, different CRM, different idea of what a good conversation looks like. The core platform does not change for each of them. You are the layer that makes it fit, and you are the one the client meets.

You are encouraged to spend time in stores. The engineers who do the best work here are the ones who have stood on a shop floor and watched where the pitch and the pipeline actually break. Nobody will make you go. You will also spend real time in the codebase, because you fix what you find rather than filing it.

What you build has a commercial edge to it. A pilot converts when the client sees the result they were promised, and an account grows when a second team inside it sees what is already sitting in their data. Both of those outcomes are yours to deliver, not somebody else's to chase.

How you will work

You design the deployment, you build it, and you own whether it holds up on a Saturday evening in a crowded store. Nobody hands you the plan, and nobody hands you the spec. You write both.

The decisions are yours. Which integration is worth the week, which vertical taxonomy needs building, what ships in the pilot and what waits, and when to tell a client that the thing they are asking for is the wrong thing to build. You go and find out what a client needs before anyone writes a line of code.

You will not be doing it alone. There are founders, AI engineers and product people around you, and they will build alongside you. What nobody will do is tell you what the client needs. That call is yours.

The work compounds if you do it well. What you learn on one deployment becomes a specification, then code, then a pattern the next one starts from. A year in, the deployments you designed should be running without you, and a new client should take a fraction of the time the first one did.

What you will do

Own the deployment end to end. Device provisioning, store connectivity, data flowing, first insight in front of the client. Get from kickoff to something real inside

the pilot window, and know by the halfway mark whether it is in trouble.

Get their HQ using it. A dashboard nobody opens is a failed deployment. Sit with the sales, marketing and L&D teams, show them what is in their own data, and

make sure the people who asked for this are actually looking at it every week.

Make the AI work on their floor. Their languages, their store noise, their product vocabulary. Benchmark transcription and speaker separation on their actual

audio, and fix what fails instead of explaining it away.

Build the vertical. Intent taxonomies, objection maps and prompt libraries for the category you are deployed into. A jewellery floor and an electronics floor do not

share a conversation model.

Wire it into their systems. CRM and POS integrations, so conversation data connects to what actually got sold and the insight can be checked against reality.

Build what the client asks for. Custom reports, dashboards and agents. Ground everything in source conversations and verify it before it ships, because a confident

wrong number costs an account.

Close the pilot. A pilot converts on results, not on effort. Know what the client agreed to judge this on, work backwards from it, and make sure the output in front of

their leadership at the end is the thing they asked for.

Grow the account. The same intelligence is worth something to marketing, L&D and category teams inside the same client. Spot which of them would benefit, show them what is already in their data, and hand a real opening to the account team.

Push it back into the product. Turn one-off client work into something the platform does by default, so the next deployment starts further ahead than this one did.

What we are looking for

Must have

• 0 to 5 years of experience. A consulting internship or an analyst role is the closest match to what this job actually asks for, but we care more about what you can do than where you did it
• Coding ability, ideally Python. Degree, internship, first job or your own projects. What we want to see is something you built that other people actually used
• Excel or Sheets at a real working level. A lot of the first conversation with a client happens in a spreadsheet before it ever happens in a dashboard
• The ability to explain a complicated idea simply. You will be taking AI output to people who do not think about models, and the explanation matters as much as the result
• Comfort at the boundaries. APIs, data pipelines, some frontend, some hardware when a device misbehaves
• An eye for where a deployment turns into more business, and the willingness to raise it yourself
• Heavy hands-on LLM usage. Prompts, evaluations, retrieval, and a clear view on where these tools break
• Fluent English and Hindi. A third Indian language counts for a lot, since the useful conversations happen on store floors and not only in HQ meeting rooms
• The instinct to go and find out what a client needs rather than waiting to be told

Good to have

Speech or audio work. Transcription, diarization, voice activity detection, or

anything that survives noisy real-world recording

Embedded or IoT experience, on ESP32 or similar

SQL and experience building things customers actually look at

Side projects, hackathons or internships where you shipped without a spec

and it worked

Production Support SRE Engineer with AI/ML

Hybrid (3 days from Office)

Years of exp: 8+ yrs

Mandate skills: Production Support, Site Reliability Engineering (SRE), hands on AI Infra setup and maintenance exposure with both OnPrem (GPU) and Cloud.

Job Details:

Primary: Production Support Engineering, Site Reliability Engineering (SRE), GCP, AI/ML Platform

Secondary skills: Python, Linux/Unix, GPU Infrastructure, GenAI Support, Splunk, AppDynamics, Hadoop/Spark, Automation Engineering

Responsibilities:

• Responsible for support functions and driving the execution of multiple Application/Platform support services including incident triage, root cause analysis, change evaluation-execution-validation,

deployment management, BCP and risk & vulnerability management, patching, monitoring.

• Provides on-call production support of Mission Critical applications and resolve issues within RTO.
• Leverage diagnostic tools to maintain, troubleshoot and restore service or data to systems  
• Bring in engineering, operational management in various domains like AI & Cloud                                                          
• Leverage AI-enabled applications, tools, Large Language Models (LLMs), Generative AI, Agentic AI frameworks, and Retrieval-Augmented Generation (RAG) architectures
• Champion continuous improvement to drive stability and operational excellence
• Work with SRE mindset. Building Automated solutions for daily redundant production support activities.
• Ability to understand and escalate issues efficiently and appropriately. Identify system bottlenecks and opportunities for process improvements
• Communicate, co-ordinate and collaborate with multiple support teams and stakeholders