Client Partnership - Sales

Position - News Editor

We are looking for a passionate News editor to join our editorial team and add flavor to the news articles. Every day, the role would include coordinating with an enthusiastic team of web3 experts in drafting articles that resonate with the target audience.

Experience: 4+ years of experience.

Roles and responsibilities

• Oversee and manage the daily operations of the newsroom, ensuring the timely publication of news articles.
• Helping and assisting the digital marketing team in framing content strategies.
• Source, assign, and review news articles, ensuring accuracy, clarity, and adherence to editorial guidelines.
• Monitor industry trends, breaking news, and regulatory updates to ensure comprehensive coverage.
• Collaborate with the social media and multimedia teams to enhance content distribution.
• Manage newsroom workflows, set deadlines, and provide editorial direction to the team.
• Conduct meticulous final checks to catch any errors, inaccuracies, or formatting issues.
• Collaborate with writers to address feedback and make necessary revisions.
• Utilize content management systems (CMS) to publish and schedule articles and multimedia content.

Note:-

Preference

• Experience in working with a team of journalists or any news media platform related to fintech.
• Experience in finding and fetching trending news using social media channels like Twitter, Reddit, Telegram, and other open-source platforms.
• Exposure to modern technologies like AI, blockchain, and Web3.

Requirements

• Bachelor's degree in Journalism, English, Communications, or a related field.
• Proven experience as an editor in a crypto media platform.
• Exceptional command of the English language, with strong writing and editing skills.
• Proficiency in using content management systems (CMS).

Founding Engineer (Bangalore)

The problem:

Business enterprises overpay vendors - on every batch of invoices, on every month because the data that would catch lives in different systems. We are building an AI agent that processes invoices end-to-end, reasons across all the relevant sources, flags genuine discrepancies, and acts - without a human having to investigate each one.

What you will own

Everything engineering. Schema design to deployment to the 2am fix when something breaks in production. There is no tech lead above you. There is no platform team. There is the architecture, you, and the founders. Concretely, this means building:

• A multi-stage agentic pipeline that takes a vendor invoice and produces a structured decision - fully autonomous for clear cases, escalating to human review for genuinely ambiguous ones. We use LangGraph, but if you've built equivalent systems with Temporal, Prefect, or custom state machines with LLM orchestration, that works
• An LLM-powered extraction layer that handles real invoices - scanned PDFs, stamped documents, inconsistent layouts - and returns structured output
• A graph data model that connects invoices to various sources and can traverse those relationships to detect discrepancies
• ERP connectors, GST validation logic, and a write-back layer that closes the loop

What we need

• Strong Python. Async FastAPI, clean service boundaries, tests that actually catch bugs. You have shipped Python backends that handled real production load
• Solid Postgres. Complex queries, schema design, migrations without downtime, row-level security for multi-tenant data. pgvector is a plus - if not, you pick it up fast
• LLM API experience in production. You have called an LLM API for something that real users depended on. You know about structured output, retry logic, cost management, prompt versioning. A side project counts if it was genuinely deployed
• Comfort with graph data models. You understand when a graph is the right structure and when it is not. You do not need deep Neo4j production experience - you need to understand graph relationships conceptually and be willing to learn Cypher. It is a 2-day ramp for the right person
• Working knowledge of deployment. Deployed and operated production workloads on GCP. Cloud Run, Cloud SQL, Cloud Storage, Redis — you're comfortable across the stack. If you've done it on AWS, the translation isn't hard, but GCP is where we are
• You own things. Not "I contributed to" - you designed it, shipped it, and fixed it when it broke. That pattern needs to be visible in your history

Good to have, not mandatory

• Built an agentic pipeline with multiple stages
• Any fintech, P2P domain experience - even tangential
• Worked at a startup with under 20 people
• Has a GitHub, blog, or writeup that shows how you think about a hard technical problem

What you get

• The hardest engineering problem you would have worked on. This is not CRUD with an LLM bolted on
• Real ownership. First engineering hire. Your architectural decisions will be in this product five years from now
• Equity that matters. ESOP - Open to discussion. We are pre-seed - this is a bet, not a guarantee. We will not pretend otherwise
• No meetings tax. You work directly with the founders. The product is specified clearly. You know what you are building and why

Honest about stage: We do not have a production ready infra yet. We have a complete architecture specification and a working prototype. If you need the stability of an established engineering org, this is not the right moment. If you want to build something real from zero and own a meaningful piece of it, it is.

The founders

One of us has spent 20 years building revenue and operational engines at companies where there was no playbook - part of the pilot team that established the world's largest search company's direct sales operations in India, managed global operations for a global mobile advertising platform, scaled a B2C platform to become one of India’s leading edtech platforms and most recently worked on building an enterprise Agentic Voice AI platform. The other has spent 15 years taking AI from demo to production in domains where failure is expensive - voice, lending, and conversational systems across a Series D conversational AI company, a major telco, a Big 4, and a leading NBFC.

Two IIT/IIM alumni who have both watched AI work in enterprise, and know exactly what it takes to get it there. We are not building this product because it sounds interesting. We are building it because we have both sat across the table from CFOs who know they are losing margin and have no tool capable of doing anything about it.

Required Skills & Qualifications

● Strong hands-on experience with LLM frameworks and models, including LangChain,

OpenAI (GPT-4), and LLaMA

● Proven experience in LLM orchestration, workflow management, and multi-agent

system design using frameworks such as LangGraph

● Strong problem-solving skills with the ability to propose end-to-end solutions and

contribute at an architectural/system design level

● Experience building scalable AI-backed backend services using FastAPI and

asynchronous programming patterns

● Solid experience with cloud infrastructure on AWS, including EC2, S3, and Load

Balancers

● Hands-on experience with Docker and containerization for deploying and managing

AI/ML applications

● Good understanding of Transformer-based architectures and how modern LLMs work

internally

● Strong skills in data processing and analysis using NumPy and Pandas

● Experience with data visualization tools such as Matplotlib and Seaborn for analysis

and insights

● Hands-on experience with Retrieval-Augmented Generation (RAG), including

document ingestion, embeddings, and vector search pipelines

● Experience in model optimization and training techniques, including fine-tuning,

LoRA, and QLoRA

Nice to Have / Preferred

● Experience designing and operating production-grade AI systems

● Familiarity with cost optimization, observability, and performance tuning for

LLM-based applications

● Exposure to multi-cloud or large-scale AI platforms

Azure DevOps engineer should have a deep understanding of container principles and hands-on experience with Docker. 

They should also be able to set-up and manage clusters using Azure Kubernetes Service (AKS). Additionally, understanding of API management, Azure Key-Vaults, ACR, networking concepts like virtual networks, subnets, NSG, route tables. Awareness of any one of the software like Apigee, Kong, or APIM in Azure is a must. Strong experience with IaC technologies like Terraform, ARM/ Bicep Templates, GitHub Pipelines, Sonar etc.

• Designing DevOps strategies: Recommending strategies for migrating and consolidating DevOps tools, designing an Agile work management approach, and creating a secure development process
• Implementing DevOps development processes: Designing version control strategies, integrating source control, and managing build infrastructure
• Managing application configuration and secrets: Ensuring system and infrastructure availability, stability, scalability, and performance
• Automating processes: Overseeing code releases and deployments with an emphasis on continuous integration and delivery
• Collaborating with teams: Working with architect and developers to ensure smooth code integration and collaborating with development and operations teams to define pipelines.
• Documentation: Producing detailed Development Architecture design, setting up the DevOps tools and working together with the CI/CD specialist in integrating the automated CI and CD pipelines with those tools
• Ensuring security and compliance/DevSecOps: Managing code quality and security policies
• Troubleshooting issues: Investigating issues and responding to customer queries
• Core Skills: Azure DevOps engineer should have a deep understanding of container principles and hands-on experience with Docker. They should also be able to set-up and manage clusters using Azure Kubernetes Service (AKS). Additionally, understanding of API management, Azure Key-Vaults, ACR, networking concepts like virtual networks, subnets, NSG, route tables. Awareness of any one of the software like Apigee, Kong, or APIM in Azure is a must. Strong experience with IaC technologies like Terraform, ARM/ Bicep Templates, GitHub Pipelines, Sonar,
• Additional Skills: Self-starter and ability to execute tasks on time, Excellent communication skills, ability to come up with multiple solutions for problems, interact with client-side experts to resolve issues by providing correct pointers, excellent debugging skills, ability to breakdown tasks into smaller steps.

Position: Automation Test Engineer

Location: TJC India, Pune

Job description:

This position involves Software Quality Assurance activities in all phases of the software development life cycle. We are looking for experienced Automation Quality Assurance engineer for SAP cloud-based application, who can carry on End-to-End testing of a newly developed Product and has Strong experience in designing test plans, test cases and test scenarios. Develop and generate scripts for Automating Test cases. Testing Methodologies Involved in manual testing includes functional testing, integration testing, User interface testing and Regression testing. Good understanding of software quality processes and practices is a must.

Required Candidate profile:

• 4-7 years of application Automation & Manual Testing experience.
• Responsible for testing of web based/SAP UI5 and other applications.
• Create detailed Test Plans, Test scenarios and Test cases.
• Experience in API and End-to-End Functional Test Automation. 
• Experience in writing Automation Tests using object-oriented programming in C#.
• Ensure proper version control and configuration management of all test objects developed and test environments use
• Develop and generate scripts to perform automated testing using selenium, Cucumber, Spec Flow etc.
• Execute and analyze automation test results.
• Raise bugs, reproduce failed scenarios, help in resolving bugs
• Familiarity with HTML, XML, Java Script, JSON, Ajax, jQuery
• Familiarity with Version Control GIT, TFS, SVN, at least one.
• Excellent communication skills (written and spoken)
• Highly self-motivated, with ability to work both independently and in a team.
• Interact with team members to develop a strong understanding of the project and testing objectives.
• Strong attention to detail with good understanding of QA concepts and methodologies.

Good to have: -

• JMeter, LoadRunner performance testing experience.
• Knowledge of QUnit, SAP/UI5, SAP UI Verify testing frameworks.
• Familiarity with Azure DevOps, Test Case management.
• Experience with Agile Scrum development methodologies would be a plus.

Required Skills: -

UI Testing, Regression Testing, Interface Testing Integration, Testing test Scenarios, Application Testing, Manual Testing, Functional Testing, quality analyst. Automation Testing, Selenium, Cucumber, C#, Spec Flow

• 5+ years of experience in a Data Engineer role
• Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.
• Experience with big data tools: Hadoop, Spark, Kafka, etc.
• Experience with relational SQL and NoSQL databases such as Cassandra.
• Experience with AWS cloud services: EC2, EMR, Athena
• Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
• Advanced SQL knowledge and experience working with relational databases, query authoring (SQL) as well as familiarity with unstructured datasets.
• Deep problem-solving skills to perform root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.