Remote Python lead manager Jobs – 110 Open Jobs Today

Principal Backend Engineer
Kairahire Solutions —Remote
- ₹30,00,000 - ₹50,00,000 a year
- Full-time
- Remote
- Master's degree
- AWS
- APIs
- Health insurance
- Work from home
Quick apply
2h

Other jobs to consider

Find your next job by exploring related positions.

Lead Data Engineer With Snowflake
3Pillar —Remote
If you would like more information about how your data is processed, please contact us. Flexibility & Well-being – Our remote-first approach gives you the…
AI Engineer (Gemini Enterprise)
Techolution —Remote
Join us to drive tangible business outcomes and shape the future of AI. Forbes publishes the best-selling book by our CEO, "Failing Fast?

I want to receive the latest job alerts for python lead manager in remote

By signing in to your account, you agree to SimplyHired's Terms of Service and consent to our Cookie and Privacy Policy.

Explore jobs in more locations

python lead manager jobs near remote

Back End Developer jobs in Bhubaneswar, Orissa

Back End Developer jobs in Delhi

Walk In Interview For Freshers,frontend Developer jobs in Chennai, Tamil Nadu

Front End Developer jobs in Thiruvananthapuram, Kerala

Walk In Interview, Front End Developer jobs in Gurugram, Haryana

Walkin Interview, Front End Developer Fresher jobs in Begumpet, Hyderabad, Telangana

Back End Developer jobs in Bhilai, Chhattisgarh

Back End Developer jobs in Bangalore Corporation Building, Bengaluru, Karnataka

Principal Backend Engineer

Kairahire Solutions
Remote

Quick apply

Job details

Permanent | Full-time
₹30,00,000 - ₹50,00,000 a year
2 hours ago

Benefits

Internet reimbursement
Provident Fund
Health insurance
Work from home
Paid sick time

Qualifications

Law
Kubernetes
Software deployment
GD&T
Master's degree
Microservices
RBAC
AWS
Docker
PostgreSQL
Distributed systems
Back-end development
APIs
S3
SaaS
AI
RDS database
Python
Identity & access management

Full job description

ROLE OVERVIEW
We are seeking a Principal Backend Engineer to own the scalability, reliability, and architectural evolution of an AI platform as it transitions from a prototype to a production-grade platform. This is a high-impact, high-ownership role at the intersection of distributed systems engineering and applied AI.KEY RESPONSIBILITIES

Platform Architecture & Scalability: Own end-to-end backend architecture for the AI platform; design for multi-tenant, high-throughput extraction workloads
Extraction Pipeline Engineering: Architect and evolve AI pipelines, define pipeline abstractions, registry patterns, and execution strategies that balance accuracy, latency, and LLM API cost.
Multi-Provider LLM Abstraction: Enhance and harden the unified LLM provider layer ; implement multi-key round-robin pooling, structured output schemas, tool-calling protocols, and provider failover logic.
Async Worker & Queue Architecture: Design the distributed worker system for heavy pipeline execution observable queue with dead-letter handling, retry policies, and backpressure management.
AWS Production Deployment: Lead the AWS deployment architecture (ECS/EC2, RDS PostgreSQL, S3, Bedrock, ALB, Secrets Manager, CloudWatch); define IaC, blue-green deployment strategies, and ensure the platform meets security, compliance, and data residency requirements.
API Design & Governance: Define and enforce API design standards (OpenAPI 3.1, spec-first, versioning, deprecation); own the 25+ FastAPI endpoints, request/response schema evolution, and backward compatibility guarantees.
Data Architecture: Own the PostgreSQL schema for extraction metadata (holes, dimensions, GD&T, title blocks, notes, extraction traces, batches); design indexing strategies, multi-tenant isolation, and efficient querying patterns for the document review and dataset export workflows.
Security & Compliance: Implement secure service-to-service communication, secrets management via AWS Secrets Manager, IAM role-based access for Bedrock and S3, and CORS/auth policies
Observability & Reliability: Instrument the platform with structured logging, distributed tracing (AWS X-Ray / OpenTelemetry), and CloudWatch alarms; define SLOs for pipeline throughput, LLM call latency, and extraction accuracy.
Engineering Leadership: Mentor senior engineers, conduct architecture and design reviews, set coding standards, and drive the technical roadmap for the enterprise.

REQUIRED SKILLS & EXPERIENCE

10+ years of backend engineering experience with a strong focus on distributed systems and production-grade platform design.
Expert-level Python proficiency; deep hands-on experience with FastAPI, SQLAlchemy, Pydantic v2, and async/concurrent programming (asyncio, ThreadPoolExecutor).
Proven experience designing and operating microservices at scale — including service decomposition, inter-service communication, and failure isolation strategies.
Strong PostgreSQL expertise: schema design, indexing, query optimization, multi-tenant isolation (RLS or schema-per-tenant), and migration management.
Hands-on AWS production experience: EC2/ECS, RDS, S3, ALB, IAM, Secrets Manager, CloudWatch, and ideally Amazon Bedrock.
Deep understanding of event-driven and async architectures: message queues, polling workers, idempotency guarantees, retry strategies, and backpressure handling.
Experience integrating LLM APIs (any of: Anthropic Claude, OpenAI, Google Gemini, Mistral, AWS Bedrock) in production — including rate limiting, structured output enforcement, and multi-provider failover.
Experience with container-based deployments using Docker and Docker Compose; familiarity with ECS task definitions and service orchestration.
Strong API lifecycle management skills: OpenAPI 3.1, versioning, backward compatibility, deprecation policies, and governance frameworks.
Practical knowledge of distributed system patterns: sagas, circuit breakers, idempotency keys, at-least-once delivery, and graceful degradation.
Security engineering fundamentals: OAuth2, JWT, RBAC, CORS, secrets management, and cloud IAM role design.
Prior experience building developer platforms, internal tooling, or AI/ML serving platforms at large-scale organizations.

PREFERRED / GOOD TO HAVE

Direct experience building AI/LLM extraction pipelines — structured output, tool-calling, multi-agent orchestration (LangGraph, CrewAI, or custom frameworks).
Familiarity with agentic pipeline patterns: planner-executor swarms, multi-round tool-use loops, shared notepad patterns, and confidence-based validation.
Experience with Amazon Bedrock cross-region inference and IAM-based model access (Amazon Nova, Claude via Bedrock).
Knowledge of ML model serving infrastructure: HuggingFace Transformers, PyTorch model loading, YOLO/object detection integration, ChromaDB vector stores.
Experience with PDF processing pipelines: rasterization (PyMuPDF), coordinate normalization, multi-page extraction, and bounding box annotation workflows.
Familiarity with service mesh (Istio/Linkerd), Kubernetes, or EKS for cloud-native deployment evolution.
Experience with workflow orchestration frameworks (Temporal, Airflow, or equivalent) for long-running, stateful extraction jobs.
Experience in high-scale SaaS platforms with strict SLAs, multi-region deployments, and enterprise security requirements.

Pay: ₹3,000,000.00 - ₹5,000,000.00 per year

Benefits:

Health insurance
Internet reimbursement
Paid sick time
Provident Fund
Work from home

Work Location: Remote

Quick apply

Refine Your Search

python lead manager jobs in remote

Principal Backend Engineer

Other jobs to consider

I want to receive the latest job alerts for python lead manager in remote

Related Searches

Explore jobs in more locations

Jobseeker tools

Employer Tools

Browse

Stay Connected