About Arcana

Arcana is a portfolio intelligence platform used by hedge funds and asset managers to analyze performance and risk. We’re rethinking the tools institutional investors rely on—and we’re hiring analysts who want to drive that transformation.

What You’ll Do

1. Build & Scale High-Impact Teams

• Hire, develop, and lead top-tier engineering talent across functions.
• Cultivate a culture of ownership, continuous learning, and psychological safety.
• Define team structure and evolve org design as we scale.

2. Drive Technical Strategy & Execution

• Set the technical direction for Arcana’s core platform and infrastructure.
• Own architecture decisions, technical design reviews, and system scalability.
• Ensure delivery of high-quality, performant, and reliable software.

3. Lead Engineering Delivery at Scale

• Own execution of major engineering initiatives with predictable timelines.
• Partner closely with Product, Design, and Business teams to align on outcomes.
• Improve velocity while maintaining high engineering standards.

4. Champion Engineering Excellence

• Define and enforce best practices in code quality, CI/CD, testing, and documentation.
• Proactively reduce technical debt and improve system robustness.
• Lead operational excellence: sprint planning, retrospectives, release cycles.

5. Coach & Develop Talent

• Mentor senior engineers from Tier 1 schools & companies
• Lead performance conversations, feedback cycles, and career development plans.
• Foster a team environment where everyone is empowered to do their best work.

What We’re Looking For

• 10+ years of software engineering experience, with at least 5 years in engineering leadership roles. Led engineering teams of 20+ people, including both ICs and EMs, across multiple domains.
• Proven ability to lead teams that ship high-quality products in fast-paced environments.
• Strong technical foundation in scalable systems, distributed architectures, and modern web technologies.
• Track record of building and scaling teams in high-growth or startup settings.
• Exceptional communication, collaboration, and cross-functional influencing skills.
• High ownership mindset with strong bias for action and outcomes.

Staff Software Engineer (Data Platform)
Join our dynamic team at the forefront of cutting-edge technology as we seek a seasoned Staff Data Engineer. Embark on a journey where your deep-rooted expertise in distributed systems, data architectures, and large-scale processing becomes the cornerstone of building high-performance data platforms. This pivotal role demands proficiency in designing and scaling compute and I/O-intensive data systems, ensuring reliability, efficiency, and cost optimization across the data lifecycle.

Responsibilities:
● Design and build scalable data platform components for batch and real-time data processing.
● Architect, develop, and operationalize large-scale data systems across ingestion, transformation, and serving layers.
● Build and manage robust data pipelines ensuring high reliability, scalability, and cost efficiency.
● Develop reusable frameworks and tooling to accelerate productivity for data engineers and data scientists.
● Leverage expertise in Python, Airflow, SQL, and cloud platforms to build production-grade data solutions.
● Optimize query performance and data models using strong understanding of columnar OLAP systems such as ClickHouse, Doris, and StarRocks.
● Implement streaming and near real-time data processing systems.
● Translate complex business requirements into scalable and efficient data platform solutions.
● Work collaboratively with cross-functional teams and provide technical leadership and mentorship.
● Drive architectural decisions by evaluating tradeoffs and selecting the right tools for the problem.

Requirements:
● Bachelor's Degree in Computer Science, Information Technology, or a similar discipline.
● 8+ years of professional experience in data engineering, backend systems, or distributed systems.
● Proven experience building scalable data platforms and large-scale data systems.
● Strong experience with ETL pipelines, data integration, and workflow orchestration systems such as Airflow or Temporal.
● Hands-on experience in Python and SQL with strong understanding of data warehouse concepts.
● Experience working with distributed OLTP/OLAP databases such as ClickHouse, PostgreSQL, Cassandra, or Elasticsearch.
● Knowledge of messaging and streaming systems such as Kafka.
● Experience with cloud platforms (AWS/GCP) and big data tools such as Spark.
● Strong understanding of columnar storage systems and query optimization techniques.
● Solid understanding of distributed systems fundamentals and associated tradeoffs.
● Experience working with containers and orchestration tools such as Docker and Kubernetes.
● Strong Linux fundamentals and system-level debugging skills.
● Familiarity with modern data architectures such as Lakehouse (Iceberg, Hudi, Delta) is a plus.

Title: Senior AI Engineer — Inference & Agent Systems

Location:
- BLR/Remote India

What We're Building

Arcana is building AI agents that synthesize information across heterogeneous sources and deliver structured, reasoned answers in real time. The product only works if the agents are fast, reliable, and correct, not approximately correct.

Our stack: Go + Temporal for orchestration, a Plan-Execute-Synthesize agent architecture, and an evaluation harness we use to measure every regression. The problems are hard. The latency bar is aggressive. The accuracy requirements are unforgiving.

The Work

Inference Optimization

- Drive TTFT below 400ms for multi-step agent pipelines

- Streaming optimization: first token to user while sub-agents are still running

- KV cache strategy, prompt compression, dynamic context window management

- Multi-provider routing: model selection by latency, cost, and task type across OpenAI, Anthropic, Gemini, and open-weight models

Agent Architecture

- Design and implement Plan-Execute-Synthesize pipelines that run sub-agents in parallel DAGs, not sequential chains

- Build reliable orchestration on top of Temporal: retries, timeouts, partial failure recovery, idempotency

- Structured output enforcement: JSON schema validation, retry loops on malformed LLM output, graceful degradation

- Tool call design: schema design that LLMs actually follow reliably across providers

Evaluation & Harness

- Own the eval framework end to end: ground truth datasets, automated scoring pipelines, regression detection on every PR

- LLM-as-judge pipelines for qualitative output assessment

- Latency regression testing - p50/p95/p99 tracked across every deployment

- Adversarial test case design: ambiguous queries, missing data, conflicting sources, malformed tool responses

Infrastructure

- Model serving and cold start optimization

- Async worker architecture for parallel sub-agent execution

- Observability: trace every token, every tool call, every synthesis step

What We're Looking For

You've built something that runs in production at a meaningful scale and you understand why it's fast (or why it isn't).

Strong signal:

- You've worked on inference pipelines where TTFT was the primary metric and you moved it meaningfully

- You've built multi-step agent systems and you know where they break not from reading papers but from watching them fail in production

- You've written eval harnesses from scratch and you have opinions about what makes a ground truth dataset actually useful

- You've debugged LLM non-determinism in production and built systems resilient to it

- You've worked with streaming LLM responses and built infrastructure around partial output handling

Weaker signal (but not disqualifying):

- You've fine-tuned models but haven't shipped inference systems

- You've used LangChain/LlamaIndex but haven't built the layer underneath

- Strong ML research background without systems exposure

Stack familiarity (we care more about depth than match): Go, Python, Temporal, Kafka, PostgreSQL, Docker

Why This Role

The problems here don't have blog posts about them yet. Parallel agent DAG execution under hard latency budgets, streaming synthesis across partial sub-agent results, eval harnesses for non-deterministic multi-step systems: these are genuinely unsolved at production quality. Small team. High ownership. Every engineer's decisions ship to production.

Who We Want to Hear From

You've shipped inference systems at:

- A real-time AI product (search, coding assistant, chat at scale)

- A model serving infrastructure company

- An agent platform (any domain)

Or you've built eval/harness infrastructure that a team of 10+ engineers actually trusted to catch regressions.

Apply

Send to: [careers@arcana.io]

1. One system you built where latency was the primary constraint what you measured, what you changed, what moved
2. Link to anything public (code, writing, talks)
3. No cover letter required

We respond to every application.

Title: Applied AI Engineer — Inference & Agent Systems

Location:
United States

What We're Building

Arcana is building AI agents that synthesize information across heterogeneous sources and deliver structured, reasoned answers in real time. The product only works if the agents are fast, reliable, and correct, not approximately correct.

Our stack: Go + Temporal for orchestration, a Plan-Execute-Synthesize agent architecture, and an evaluation harness we use to measure every regression. The problems are hard. The latency bar is aggressive. The accuracy requirements are unforgiving.

The Work

Inference Optimization

- Drive TTFT below 400ms for multi-step agent pipelines

- Streaming optimization: first token to user while sub-agents are still running

- KV cache strategy, prompt compression, dynamic context window management

- Multi-provider routing: model selection by latency, cost, and task type across OpenAI, Anthropic, Gemini, and open-weight models

Agent Architecture

- Design and implement Plan-Execute-Synthesize pipelines that run sub-agents in parallel DAGs, not sequential chains

- Build reliable orchestration on top of Temporal: retries, timeouts, partial failure recovery, idempotency

- Structured output enforcement: JSON schema validation, retry loops on malformed LLM output, graceful degradation

- Tool call design: schema design that LLMs actually follow reliably across providers

Evaluation & Harness

- Own the eval framework end to end: ground truth datasets, automated scoring pipelines, regression detection on every PR

- LLM-as-judge pipelines for qualitative output assessment

- Latency regression testing - p50/p95/p99 tracked across every deployment

- Adversarial test case design: ambiguous queries, missing data, conflicting sources, malformed tool responses

Infrastructure

- Model serving and cold start optimization

- Async worker architecture for parallel sub-agent execution

- Observability: trace every token, every tool call, every synthesis step

What We're Looking For

You've built something that runs in production at a meaningful scale and you understand why it's fast (or why it isn't).

Strong signal:

- You've worked on inference pipelines where TTFT was the primary metric and you moved it meaningfully

- You've built multi-step agent systems and you know where they break not from reading papers but from watching them fail in production

- You've written eval harnesses from scratch and you have opinions about what makes a ground truth dataset actually useful

- You've debugged LLM non-determinism in production and built systems resilient to it

- You've worked with streaming LLM responses and built infrastructure around partial output handling

Weaker signal (but not disqualifying):

- You've fine-tuned models but haven't shipped inference systems

- You've used LangChain/LlamaIndex but haven't built the layer underneath

- Strong ML research background without systems exposure

Stack familiarity (we care more about depth than match): Go, Python, Temporal, Kafka, PostgreSQL, Docker

Why This Role

The problems here don't have blog posts about them yet. Parallel agent DAG execution under hard latency budgets, streaming synthesis across partial sub-agent results, eval harnesses for non-deterministic multi-step systems: these are genuinely unsolved at production quality. Small team. High ownership. Every engineer's decisions ship to production.

Who We Want to Hear From

You've shipped inference systems at:

- A real-time AI product (search, coding assistant, chat at scale)

- A model serving infrastructure company

- An agent platform (any domain)

Or you've built eval/harness infrastructure that a team of 10+ engineers actually trusted to catch regressions.

Apply

Send to: [careers@arcana.io]

Include:

1. One system you built where latency was the primary constraint what you measured, what you changed, what moved
2. Link to anything public (code, writing, talks)
3. No cover letter required

We respond to every application.

As our Lead Security Engineer, you'll own and elevate Arcana's overall security posture - cloud, on-prem, and everything in between. You'll design and enforce policies, automate controls, and harden infrastructure end-to-end. While your primary focus will be on our GCP resources, you'll also partner with teams across networking, applications, and compliance to ensure we're secure by design and resistant to drift.

Responsibilities:

• Enterprise Security Architecture - Governance and Compliance, including driving adherence to ISO 27001, SOC 2, GDPR, and enforcing CIS benchmarks on all infrastructure.
• Policy, Automation, and Guardrails - own the end-to-end security lifecycle by defining policy-as-code, embedding continuous compliance checks into CI/CD, and building automated, drift-resistant guardrails across cloud, containers, and VMs.
• Infrastructure Hardening and Drift Detection - implement automated drift alerts and self-healing playbooks for VPCs, firewall rules, Kubernetes clusters, and endpoints.
• Monitoring, Logging, and Incident Response - configure Cloud Audit Logs, SIEM exports, and custom alerts for critical security events; lead root-cause investigations, build detection logic, and develop runbooks for cloud-wide incidents.

Requirements:

• 5+ years driving security and compliance in dynamic, regulated environments- securing cloud-native platforms and hybrid infrastructures, with deep familiarity in fintech and portfolio-management standards, and best practices for supporting distributed, remote teams.
• Deep expertise with GCP security (IAM, KMS, VPC Service Controls, Cloud Logging/Audit, WAF, SecOps) and Kubernetes application hardening.
• Strong Infrastructure-as-Code skills (Terraform or equivalent) and GitOps experience (ArgoCD, Flux).
• Proficiency in Python scripting and policy-as-code frameworks (OPA, Gatekeeper).
• Excellent communicator - able to translate technical findings into clear policies and remediation plans.

Helpful Experience:

• Familiarity with multi-cloud security controls.
• Security certifications (GCP Professional Security Engineer, CISSP, CKA/CKS).
• Experience with service mesh (Istio/Anthos) or zero-trust architectures.

As our Lead Security Engineer, you'll own and elevate Arcana's overall security posture - cloud, on-prem, and everything in between. You'll design and enforce policies, automate controls, and harden infrastructure end-to-end. While your primary focus will be on our GCP resources, you'll also partner with teams across networking, applications, and compliance to ensure we're secure by design and resistant to drift.

Responsibilities:

• Enterprise Security Architecture - Governance and Compliance, including driving adherence to ISO 27001, SOC 2, GDPR, and enforcing CIS benchmarks on all infrastructure.
• Policy, Automation, and Guardrails - own the end-to-end security lifecycle by defining policy-as-code, embedding continuous compliance checks into CI/CD, and building automated, drift-resistant guardrails across cloud, containers, and VMs.
• Infrastructure Hardening and Drift Detection - implement automated drift alerts and self-healing playbooks for VPCs, firewall rules, Kubernetes clusters, and endpoints.
• Monitoring, Logging, and Incident Response - configure Cloud Audit Logs, SIEM exports, and custom alerts for critical security events; lead root-cause investigations, build detection logic, and develop runbooks for cloud-wide incidents.

Requirements:

• 5+ years driving security and compliance in dynamic, regulated environments- securing cloud-native platforms and hybrid infrastructures, with deep familiarity in fintech and portfolio-management standards, and best practices for supporting distributed, remote teams.
• Deep expertise with GCP security (IAM, KMS, VPC Service Controls, Cloud Logging/Audit, WAF, SecOps) and Kubernetes application hardening.
• Strong Infrastructure-as-Code skills (Terraform or equivalent) and GitOps experience (ArgoCD, Flux).
• Proficiency in Python scripting and policy-as-code frameworks (OPA, Gatekeeper).
• Excellent communicator - able to translate technical findings into clear policies and remediation plans.

Helpful Experience:

• Familiarity with multi-cloud security controls.
• Security certifications (GCP Professional Security Engineer, CISSP, CKA/CKS).
• Experience with service mesh (Istio/Anthos) or zero-trust architectures.

• We're seeking a passionate Manual QA Engineer to drive the quality and performance of our software products. You'll take charge of test plans, hunt down bugs, and collaborate with development and product teams to ensure high-quality releases. Your work will be key in maintaining the high standards of our platform and enabling product development at Arcana.

  
  Responsibilities:
  • Design and execute comprehensive manual test plans and test cases for web applications.
  • Conduct functional, regression, integration, and system testing across multiple platforms.
  • Identify, report, and track defects, ensuring timely resolution in collaboration with the development team.
  • Ensure that products meet user requirements and perform well under different scenarios and conditions.
  • Work closely with developers and product managers to understand requirements and provide feedback on design and usability.
  • Provide thorough documentation for test procedures and results.
  • Assist in the continuous improvement of QA processes and methodologies.
  Requirements:
  • Bachelor's degree in Computer Science, Engineering, or related field.
  • 2+ years of experience in manual testing of web-based applications.
  • Strong understanding of software testing methodologies, tools, and processes.
  • Experience in writing clear, concise, and comprehensive test cases and test plans.
  • Familiarity with bug-tracking tools such as Linear or JIRA.
  • Knowledge of SQL and experience in database testing.
  • Good understanding of web technologies (HTML, CSS, JavaScript) and APIs.
  • Strong problem-solving skills with attention to detail.
  • Excellent communication and collaboration skills.
  • Preferred:
  • Experience in testing financial or analytics software.
  • Familiarity with Agile methodologies.

Join our dynamic team at the forefront of cutting-edge technology as we seek a seasoned DevOps Engineer (Bangalore, Coimbatore). Embark on a journey where your deep-rooted expertise in computer science fundamentals, alongside an intricate understanding of data structures, algorithms, and system design, becomes the cornerstone of innovative solutions. This pivotal role not only demands your proficiency in developing and elevating compute and I/O-intensive applications but also ensures their peak performance and unwavering reliability.

Responsibilities:

• Own design and implementation of infrastructure services including GCP cloud architecture.
• Build and maintain highly automated infrastructure using tools like Terraform, Ansible, and scripting (Python/Go).
• Drive improvements in system reliability, performance monitoring, logging, and alerting systems.
• Ensure systems are secure by design—manage access controls, secrets, and network segmentation with a strong security-first mindset.
• Build internal tooling and CI/CD pipelines to accelerate developer productivity.
• Collaborate with engineering leaders and mentor a growing team of infrastructure engineers.
• Work closely with application teams, product managers, and leadership to align infrastructure efforts with Arcana’s technical roadmap.

Requirements:

• 4 + years of hands-on experience in DevOps/Infrastructure Engineering roles, preferably at high-growth tech startups or product companies.
• Deep expertise in Linux systems, distributed systems, containers, Kubernetes, and cloud (preferably GCP/AWS).
• Strong programming skills in Python, Go, or similar languages; scripting expertise is a must.
• Proven experience with infrastructure-as-code, automation, CI/CD (e.g., GitHub Actions, ArgoCD, Jenkins), and monitoring tools like Prometheus, ELK, or Grafana.
• Strong focus on security, reliability, and performance in high-availability environments.
• Leadership experience or strong mentorship history, comfortable driving architectural decisions and influencing engineering culture.
• Excellent communication skills; ability to work cross-functionally with both technical and non-technical teams.
• Experience scaling infrastructure for fast-growing startups
• Exposure to cloud-native security practices and zero-trust architectures
• Background in developer platforms or internal tooling
• Familiarity with data-heavy or ML-based system
• Passion for elegant tooling and developer enablement
  
  

We're looking for a dynamic Senior Data Scientist to join our team, working alongside our founders, financial analysts, product managers, and engineers. This is your chance to get hands-on with massive datasets, crafting the metrics that matter to institutional investors worldwide. For those who are curious and passionate about financial technologies, this is a great opportunity to work at an extremely well-capitalized startup with a proven team of senior financial and tech industry talent to build the future of investing tools.

Responsibilities:

• Work with large and complex data sets and derive investment-relevant metrics in close partnership with financial analysts and engineers.
• Apply knowledge of statistics, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to the development of fundamental metrics needed to evaluate various assets.
• Implement the risk factor model using advanced statistical and programming techniques, ensuring its performance aligns with the proposed design.
• Conduct rigorous testing and validation of the model to ensure its effectiveness in identifying, quantifying, and managing various risk factors.
• Build customer-facing metrics and dashboards.
• Work closely with analysts, engineers, and Product Managers and provide feedback as we develop our data analytics and research platform.

Requirements:

• Bachelor's degree in Mathematics, Statistics, a relevant technical field, or equivalent practical experience (or) degree in an analytical field (e. g. Computer Science, Engineering, Mathematics, Statistics, Operations Research, Management Science). IIT preferred.
• 3+ years of experience with data analysis and metrics development.
• 3+ years of experience analyzing and interpreting data, drawing conclusions, defining recommended actions, and reporting results across stakeholders.
• 2+ years of experience writing SQL queries.
• 2+ years of experience scripting in Python.
• Interested in learning new technologies to solve customer needs with lots of creative freedom.
• Strong communication skills and business acumen.
• Self-starter, motivated by an interest in developing the best possible solutions to problems.
• Strong SQL and Python programming skills.
• Experience with Airflow, Google BigQuery, and Clickhouse is a plus.

We are looking for an IT Support Engineer to provide day-to-day on-site and remote support to employees, ensuring smooth operations across hardware, software, and core IT services. This role requires a security-first mindset, strong troubleshooting skills, and the ability to work collaboratively with teams to support business operations at scale.

Key Responsibilities

• Provide on-site and remote IT support via walk-ups, tickets, and chat.
• Deliver hardware and software troubleshooting and break-fixes for macOS and Windows systems.
• Support and maintain IT services such as MDM (Kandji), SentinelOne EDR, Google Workspace, Slack, Okta, PAM solutions, and vulnerability management tools.
• Install, configure, and maintain software, hardware, and network devices.
• Manage IT assets, including procurement, deployment, lifecycle tracking, and audits.
• Monitor and respond to security alerts, ensuring compliance with security best practices.
• Provide IT support for meeting room technology, conferencing tools, and A/V systems.
• Troubleshoot and escalate network connectivity issues (Wi-Fi, VPN, switches, access points).
• Conduct new hire onboarding and offboarding, including provisioning/deprovisioning of accounts and devices.
• Develop and maintain IT documentation, knowledge base articles, and SOPs.
• Partner with Operations and other stakeholders on IT and infrastructure projects.
• Contribute to process improvements and optimization of IT support tools and workflows.

Requirements

• Bachelor’s degree in Computer Science, Information Technology, or related field, or equivalent practical experience.
• 4-6 years of IT support or system administration experience.
• Strong knowledge of macOS and Windows environments.
• Hands-on experience with tools such as Google Workspace, Okta, Slack, MDM (Kandji), EDR (SentinelOne).
• Familiarity with asset management, IT procurement, and lifecycle management.
• Strong troubleshooting, communication, and documentation skills.
• Security-first mindset with experience handling security alerts and vulnerabilities.

Nice to Have

• Industry certifications such as CompTIA A+, Network+, Security+, or equivalent.
• Experience with PAM solutions, system vulnerability management tools, or advanced networking.
• Prior experience in a fast-paced startup environment.
• Ability to conduct IT training sessions and employee security awareness programs.

Join our dynamic team at the forefront of cutting-edge technology as we seek a seasoned Staff/Lead Backend Engineer. Embark on a journey where your deep-rooted expertise in computer science fundamentals, alongside an intricate understanding of data structures, algorithms, and system design, becomes the cornerstone of innovative solutions. This pivotal role not only demands your proficiency in developing and elevating compute and I/O-intensive applications but also ensures their peak performance and unwavering reliability.

Responsibilities:

• Architect, refine, and escalate the capabilities of complex backend systems using Python, with a laser focus on efficiency, durability, and scale.
• Elevate application performance, optimizing for speed, scalability, and resource allocation.
• Forge robust methodologies to manage high concurrency and vast data volumes, setting new industry benchmarks.
• Collaborate intimately with engineering and product peers to crystallize requirements into resilient, scalable architectures.
• Demonstrate proficiency with advanced storage solutions and databases like Redis, PostgreSQL, and ClickHouse, enhancing system integrity.
• Champion coding excellence, testing rigor, and deployment precision, driving best practices across the development lifecycle.

Requirements:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Minimum of 5 years of experience in backend development with Python in a production environment.
• Proven experience in scaling compute and I/O-intensive applications.
• Strong foundation in computer science, with a deep understanding of data structures, algorithms, and system design principles.
• Experience in handling concurrent requests at scale and optimizing large-scale systems for performance and reliability.
• Familiarity with database technologies such as Redis, PostgreSQL, and ClickHouse.
• Experience in the financial sector, particularly in developing fintech applications or systems, is a plus.
• Solid understanding of software development life cycle, continuous integration, and continuous delivery (CI/CD) practices.
• Excellent problem-solving abilities and strong communication skills.

We're looking for a passionate and experienced Lead iOS Engineer who values clean code, sound design, and collaboration. We're building a next-gen ultra-fast, secure portfolio intelligence platform that blends speed, delight, and reliability, and now, we're ready to bring that experience to iOS. This is a unique opportunity to build the first version of the iOS application from the ground up for Arcana.

Responsibilities:

• Work closely with our product, design, and engineering teams to build new and innovative application experiences for the iOS platform.
• Implement custom native user interfaces using the latest iOS programming techniques.
• Build reusable iOS software components for interfacing with our back-end platforms.
• Analyze and optimize UI and infrastructure application code for quality, efficiency, and performance.
• Analyze, debug, and optimize application code and infrastructure for performance, efficiency, and quality.
• Advocate for and implement iOS development best practices, raising engineering quality across teams.
• Continuously invest in client infrastructure to improve development velocity, app reliability, and end-user experience.
• Drive the evaluation and adoption of modern mobile frameworks and technologies.
• Foster a collaborative, growth-oriented team culture with a focus on technical excellence and continuous improvement.

Requirements:

• Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience; a Master's or PhD is a plus.
• At least 5 years of professional software development experience, focused on iOS development using Objective-C, Swift, and the iOS SDK.
• Proven experience designing, building, and maintaining complex, scalable, and testable codebases, with a strong understanding of API design and unit testing strategies.
• Solid grasp of multithreading, concurrency, and memory management in mobile environments.
• Hands-on experience with feature flagging systems, experimentation systems, and large-scale mobile application architecture.
• Strong understanding of data structures and algorithms, with a technical leadership role guiding project teams and setting architectural direction.
• Demonstrated experience working in cross-functional and matrixed environments, collaborating effectively across product, design, and engineering teams.
• Exposure to or experience with other mobile platforms is a plus (e. g., Android).

Must-Have Skill:

• Proficiency in Swift (and Objective-C).
• Strong Understanding of iOS SDK and Frameworks.
• Experience with Xcode and Interface Builder.
• App Architecture Patterns like MVVM, MVC, or Clean Architecture for scalable and maintainable code.
• RESTful APIs and Networking.
• Unit Testing and Test Automation.
• App Store Deployment and Release Cycle.