AbleCredit
https://ablecredit.comAbout
AI that writes Credit Reports on its own !!
AbleCredit is a friendly, supportive credit assistant. It generates Credit Appraisal Memos based on your policies, without any human intervention.
Candid answers by the company
AI that writes Credit Reports on its own !!
AbleCredit is your friendly, supportive credit assistant. It generates Credit Appraisal Memos based on your policies, without any human intervention.
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Jobs at AbleCredit
Role: Senior Security Engineer
Salary: INR 20-35L per annum
Performance Bonus: Up to 10% of the base salary
Location: Hulimavu, Bangalore, India
Experience: 5-8 years
About AbleCredit:
AbleCredit has built a foundational AI platform to help BFSI enterprises reduce OPEX by up to 70% by powering workflows for onboarding, claims, credit, and collections. Our GenAI model achieves over 95% accuracy in understanding Indian dialects and excels in financial analysis.
The company was founded in June 2023 by Utkarsh Apoorva (IIT Delhi, built Reshamandi, Guitarstreet, Edulabs); Harshad Saykhedkar (IITB, ex-AI Lead at Slack); and Ashwini Prabhu (IIML, co-founder of Mythiksha, ex-Product Head at Reshamandi, HandyTrain).
What Work You’ll Do
- Be the guardian of trust — every system you secure will protect millions of data interactions.
- Operate like a builder, not a gatekeeper — automate guardrails that make security invisible but ever-present.
- You’ll define what ‘secure by default’ means for a next-generation AI SaaS platform.
- Own the security posture of our cloud-native SaaS platform — design, implement, and enforce security controls across AWS, Linux, and Kubernetes (EKS) environments.
- Drive security compliance initiatives such as SOC 2 Type II, ISO 27001, and RBI-aligned frameworks — build systems that enforce, not just document, compliance.
- Architect defense-in-depth systems across EC2, S3, IAM, and VPC layers, ensuring secure configuration, least-privilege access, and continuous compliance.
- Build and automate security pipelines — integrate AWS Security Hub, GuardDuty, Inspector, WAF, and CloudTrail into continuous detection and response systems.
- Lead vulnerability management and incident readiness — identify, prioritize, and remediate vulnerabilities across the stack while ensuring traceable audit logs.
- Implement and maintain zero-trust and least-privilege access controls using AWS IAM, SSO, and modern secrets management tools like AWS SSM or Vault.
- Serve as a trusted advisor — train developers, review architecture, and proactively identify risks before they surface.
The Skills You Have..
- Deep hands-on experience with AWS security architecture — IAM, VPCs, EKS, EC2, S3, CloudTrail, Security Hub, WAF, GuardDuty, and Inspector.
- Strong background in Linux hardening, container security, and DevSecOps automation.
- Proficiency with infrastructure-as-code (Terraform, CloudFormation) and integrating security controls into provisioning.
- Knowledge of zero-trust frameworks, least-privilege IAM, and secrets management (Vault, SSM, KMS).
- Experience with SIEM and monitoring tools — configuring alerts, analyzing logs, and responding to incidents.
- Familiarity with compliance automation and continuous assurance — especially SOC 2, ISO 27001, or RBI frameworks.
- Understanding of secure software supply chains — dependency scanning, artifact signing, and policy enforcement in CI/CD.
- Ability to perform risk assessment, threat modeling, and architecture review collaboratively with engineering teams.
What You Should Have Done in the Past
- Secured cloud-native SaaS systems built entirely on AWS (EC2, EKS, S3, IAM, VPC).
- Led or contributed to SOC 2 Type II or ISO 27001 certification initiatives, ideally in a regulated industry such as FinTech.
- Designed secure CI/CD pipelines with integrated code scanning, image validation, and secrets rotation.
- (Bonus) Built internal security automation frameworks or tooling for continuous monitoring and compliance checks.
SDE 2 / SDE 3 – AI Infrastructure & LLM Systems Engineer
Location: Pune / Bangalore (India)
Experience: 4–8 years
Compensation: no bar for the right candidate
Bonus: Up to 10% of base
About the Company
AbleCredit builds production-grade AI systems for BFSI enterprises, reducing OPEX by up to 70% across onboarding, credit, collections, and claims.
We run our own LLMs on GPUs, operate high-concurrency inference systems, and build AI workflows that must scale reliably under real enterprise traffic.
Role Summary (What We’re Really Hiring For)
We are looking for a strong backend / systems engineer who can:
- Deploy AI models on GPUs
- Expose them via APIs
- Scale inference under high parallel load using async systems and queues
This is not a prompt-engineering or UI-AI role.
Core Responsibilities
- Deploy and operate LLMs on GPU infrastructure (cloud or on-prem).
- Run inference servers such as vLLM / TGI / SGLang / Triton or equivalents.
- Build FastAPI / gRPC APIs on top of AI models.
- Design async, queue-based execution for AI workflows (fan-out, retries, backpressure).
- Plan and reason about capacity & scaling:
- GPU count vs RPS
- batching vs latency
- cost vs throughput
- Add observability around latency, GPU usage, queue depth, failures.
- Work closely with AI researchers to productionize models safely.
Must-Have Skills
- Strong backend engineering fundamentals (distributed systems, async workflows).
- Hands-on experience running GPU workloads in production.
- Proficiency in Python (Golang acceptable).
- Experience with Docker + Kubernetes (or equivalent).
- Practical knowledge of queues / workers (Redis, Kafka, SQS, Celery, Temporal, etc.).
- Ability to reason quantitatively about performance, reliability, and cost.
Strong Signals (Recruiter Screening Clues)
Look for candidates who have:
- Personally deployed models on GPUs
- Debugged GPU memory / latency / throughput issues
- Scaled compute-heavy backends under load
- Designed async systems instead of blocking APIs
Nice to Have
- Familiarity with LangChain / LlamaIndex (as infra layers, not just usage).
- Experience with vector DBs (Qdrant, Pinecone, Weaviate).
- Prior work on multi-tenant enterprise systems.
Not a Fit If
- Only experience is calling OpenAI / Anthropic APIs.
- Primarily a prompt engineer or frontend-focused AI dev.
- No hands-on ownership of infra, scaling, or production reliability.
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